Alex Curran is the CEO of Aptitude Software and has spent 20 years working with CFOs at some of the world's most complex finance organizations.
In this episode, she shares why 87% of CFOs say AI matters but less than 10% can show a return, and what needs to change at the systems level before any AI strategy can deliver results.
Alex breaks down the three conversations every CFO must have with their CEO, what it actually takes to get to a zero-day close, and why putting AI on top of legacy architecture makes the problem worse, not better.
00:00:00 --> 00:00:05 87 % of CFOs have said that AI will be important
00:00:05 --> 00:00:07 to their finance operations this year. And then
00:00:07 --> 00:00:11 7%, 8 % of them were only actually able to point
00:00:11 --> 00:00:14 to any measurable return. 87 % wanted, but not
00:00:14 --> 00:00:17 even 10 % actually have it. Alex Curran is the
00:00:17 --> 00:00:20 CEO of Aptitude Software. She has spent more
00:00:20 --> 00:00:22 than a decade working with some of the world's
00:00:22 --> 00:00:25 most complex finance organizations. And today,
00:00:25 --> 00:00:28 she sits across the table from CFOs grappling
00:00:28 --> 00:00:30 with a fundamental shift in what's expected of
00:00:30 --> 00:00:33 the finance function. Over her 20 years at Aptitude,
00:00:33 --> 00:00:36 she set up the company's North American office
00:00:36 --> 00:00:38 and spent more than 10 years building its U .S.
00:00:38 --> 00:00:41 and Canadian business. The CFO ends up being
00:00:41 --> 00:00:45 caught between a CEO asking for real -time answers
00:00:45 --> 00:00:47 and a system that actually can't produce them.
00:00:47 --> 00:00:50 What's really important to that is that the AI
00:00:50 --> 00:00:52 topic in general strengthens that partnership
00:00:52 --> 00:00:56 between the CFO and the CEO. It brings them closer
00:00:56 --> 00:00:58 together because the stress is in the strains.
00:00:58 --> 00:01:01 and the asks become louder. Now, what would you
00:01:01 --> 00:01:03 say are three things that CFOs should understand
00:01:03 --> 00:01:06 about handling the pressure of delivering an
00:01:06 --> 00:01:09 AI strategy that demonstrate ROI? It's the data,
00:01:09 --> 00:01:10 not the model. I think the models are absolutely
00:01:10 --> 00:01:13 extraordinary, right? But what's failing underneath
00:01:13 --> 00:01:15 them is that the data that you see in these finance
00:01:15 --> 00:01:18 functions, it's either siloed or it's batched
00:01:18 --> 00:01:21 and summarized before AI has even ever seen it.
00:01:21 --> 00:01:23 You've got to have the right technology underneath
00:01:23 --> 00:01:26 it to support it too. Understanding the difference
00:01:26 --> 00:01:29 between what an AI native technology solutionism,
00:01:30 --> 00:01:33 one that's AI enabled, is key core fundamental.
00:01:33 --> 00:01:36 And then I think the third point would be...
00:01:38 --> 00:01:40 Today's episode is brought to you by Finipes,
00:01:41 --> 00:01:44 an AI -native finance ERP that runs finance in
00:01:44 --> 00:01:47 real time. Live piano reports drawn straight
00:01:47 --> 00:01:50 from the ledger with a full lineage to source.
00:01:50 --> 00:01:53 Anomaly detection catches problems at source,
00:01:53 --> 00:01:56 not month and close. So you can walk into the
00:01:56 --> 00:01:58 boardroom with numbers you can stand behind.
00:01:59 --> 00:02:00 Stop reporting the past and start driving the
00:02:00 --> 00:02:03 future. You can learn more at FineApps .com.
00:02:03 --> 00:02:07 app, I will drop the link in the show. Welcome
00:02:07 --> 00:02:09 back to the Dariova CFO podcast. I'm your host
00:02:09 --> 00:02:11 with Sia Kaman, a sitting CFO with a background
00:02:11 --> 00:02:13 in accounting and FP &A. I started this show
00:02:13 --> 00:02:16 because I believe the way companies build and
00:02:16 --> 00:02:18 lead their finance function determines whether
00:02:18 --> 00:02:20 they scale or fall apart. Each week I sit down
00:02:20 --> 00:02:23 with CFOs, CEOs, and strategic business partners
00:02:23 --> 00:02:25 to talk about what that actually looks like in
00:02:25 --> 00:02:27 reality. Building the right teams, getting the
00:02:27 --> 00:02:30 systems and control in place, and partnering
00:02:30 --> 00:02:32 with the business hopefully without burning out
00:02:32 --> 00:02:35 in the process. So super excited to have with
00:02:35 --> 00:02:39 me my guest, Alex Curran. She's the CEO of Aptitude
00:02:39 --> 00:02:42 Software. Alex has spent more than a decade working
00:02:42 --> 00:02:44 with some of the world's most complex finance
00:02:44 --> 00:02:48 organizations. And today, she sits across the
00:02:48 --> 00:02:51 table from CFOs, grappling with a fundamental
00:02:51 --> 00:02:54 shift in what's expected of the finance function.
00:02:54 --> 00:02:58 Yes, if you feel it, I do. Boards want faster
00:02:58 --> 00:03:01 answers. Businesses want real -time insight.
00:03:02 --> 00:03:05 AI is raising expectations again and again, yet
00:03:05 --> 00:03:08 many finance teams are still operating on accounting
00:03:08 --> 00:03:11 systems built around batch processes, fragmented
00:03:11 --> 00:03:14 data, and month -end cycles. That puts Alex in
00:03:14 --> 00:03:16 a particularly interesting position for this
00:03:16 --> 00:03:20 conversation. She sees firsthand where CFOs are
00:03:20 --> 00:03:22 struggling to close the gap between the finance
00:03:22 --> 00:03:24 function they have today and the one they are
00:03:24 --> 00:03:27 now being asked to build. We are going to talk
00:03:27 --> 00:03:30 about what CFOs are getting wrong about AI, why
00:03:30 --> 00:03:33 the underlying accounting engine has suddenly
00:03:33 --> 00:03:36 become a board level issue, and what needs to
00:03:36 --> 00:03:38 change if finance is going to move from reporting
00:03:38 --> 00:03:42 what happened to helping shape what's next. We'll
00:03:42 --> 00:03:45 also expel Fynipes after two new finance ERP
00:03:45 --> 00:03:48 and why Alex believes a new generation of finance
00:03:48 --> 00:03:52 technology is emerging to solve problems traditionally
00:03:52 --> 00:03:56 ERP were never designed for. Today she's here
00:03:56 --> 00:03:58 to give us the CEO side of the story because
00:03:58 --> 00:04:00 from where Alex is a difference between a great
00:04:00 --> 00:04:04 CFO and one who never quite lands becomes down
00:04:04 --> 00:04:07 to a few specific conversations. Today she will
00:04:07 --> 00:04:10 tell us what those three conversations are. why
00:04:10 --> 00:04:13 they matter and where most CFOs keep them. Welcome
00:04:13 --> 00:04:16 to the show, Alex. Hey, thank you. I'm delighted
00:04:16 --> 00:04:19 to be here. So yeah, thank you very much for
00:04:19 --> 00:04:23 having me on today. Of course. I'm always, always
00:04:23 --> 00:04:27 wondering how people get into the world of accounting
00:04:27 --> 00:04:30 or involved in the industry at all. So please,
00:04:30 --> 00:04:32 please take us back to your early career and
00:04:32 --> 00:04:34 what drew you to the corporate finance, what
00:04:34 --> 00:04:38 drew you to aptitude and what kept you there.
00:04:38 --> 00:04:42 Yeah, look, I think to your point, right, accounting,
00:04:42 --> 00:04:47 finance, maybe not the most overly of exciting
00:04:47 --> 00:04:53 kind of topics. But I think, you know, aptitude
00:04:53 --> 00:04:59 has always been in a number of different sectors.
00:04:59 --> 00:05:02 And I think gaining awareness of how different
00:05:02 --> 00:05:06 sectors work, how different companies operate
00:05:06 --> 00:05:10 fascinated me. And then you combine that with
00:05:10 --> 00:05:14 being able to follow my passion for sales. That's
00:05:14 --> 00:05:18 where I started. I'm a super competitive individual.
00:05:19 --> 00:05:23 I think that combination was incredibly attractive.
00:05:23 --> 00:05:28 And I think then you add to that. looking at
00:05:28 --> 00:05:31 the products that Aptitude was proposing and
00:05:31 --> 00:05:35 selling into those different sectors. We were
00:05:35 --> 00:05:39 helping organisations become compliant with different
00:05:39 --> 00:05:42 regulatory standards that they were really struggling
00:05:42 --> 00:05:46 with. And you could see the relief when you met
00:05:46 --> 00:05:47 with them, you explained that you could help,
00:05:48 --> 00:05:50 and then you proved it by actually helping them
00:05:50 --> 00:05:53 and getting them live. And that was, I think,
00:05:53 --> 00:05:56 for me, really rewarding. I think in addition
00:05:56 --> 00:06:00 to that, I'm quite pacey. I move at pace and
00:06:00 --> 00:06:06 I think aptitude has always or has a legacy of
00:06:06 --> 00:06:09 moving very quickly, moving very fast, punching
00:06:09 --> 00:06:12 above our weight and building products that the
00:06:12 --> 00:06:15 market actually wants, but actually staying ahead
00:06:15 --> 00:06:19 of the market and building something, being at
00:06:19 --> 00:06:21 the forefront of the market. being able to get
00:06:21 --> 00:06:24 ahead of the competition. So again, I think all
00:06:24 --> 00:06:27 of that combined was very attractive. And I think
00:06:27 --> 00:06:32 that has kept me there. But I also think, for
00:06:32 --> 00:06:35 me, we couldn't do any of that without the team
00:06:35 --> 00:06:38 and the people, right? So we work super hard.
00:06:39 --> 00:06:42 We believe deeply in what we're building. We
00:06:42 --> 00:06:45 enjoy it. And I think 20 years in, 20 years later,
00:06:45 --> 00:06:48 that is absolutely still what gets me out of
00:06:48 --> 00:06:51 bed. So, yeah, great question. Oh, that is awesome.
00:06:51 --> 00:06:55 Because it is quite rare to see someone 20 years
00:06:55 --> 00:06:58 at the same companies these days. So it speaks
00:06:58 --> 00:07:01 a lot to what you said around the people and
00:07:01 --> 00:07:04 the culture and also the product you keep bringing
00:07:04 --> 00:07:06 to the market. But you set up Attitudes North
00:07:06 --> 00:07:09 American Office. What would you say are some
00:07:09 --> 00:07:11 of the things you learned from that experience
00:07:11 --> 00:07:14 and have taken forward? Any culture shock? as
00:07:14 --> 00:07:17 well in the project. Yeah, great question actually,
00:07:17 --> 00:07:22 why don't I start there. Maybe not a cultural
00:07:22 --> 00:07:23 question, but definitely a language question.
00:07:23 --> 00:07:27 I think kind of everyone assumes that we both
00:07:27 --> 00:07:29 speak English, but I remember on a number of
00:07:29 --> 00:07:32 occasions kind of walking into shops and, you
00:07:32 --> 00:07:35 know, asking where the lift was or, I don't know,
00:07:35 --> 00:07:39 asking where, I don't know, actually like coriander
00:07:39 --> 00:07:43 as an example, they call it cilantro. And people
00:07:43 --> 00:07:44 were just giving me the weirdest looks because
00:07:44 --> 00:07:48 the words that we use are very, very different.
00:07:48 --> 00:07:51 So that was definitely a bit of a shock for me.
00:07:52 --> 00:07:55 But yeah, I think, back to your question, I spent
00:07:55 --> 00:07:57 quite a bit of my career, so probably 10 plus
00:07:57 --> 00:08:01 years in North America, working in the US and
00:08:01 --> 00:08:05 Canadian markets. I would say very, very grateful
00:08:05 --> 00:08:08 to have had that opportunity, even given the
00:08:08 --> 00:08:11 opportunity to go away and move out there. and
00:08:11 --> 00:08:14 grow the business and literally I moved out with
00:08:14 --> 00:08:18 a suitcase, a pad of paper and a pen and then
00:08:18 --> 00:08:22 hit the phones. So it was blood, sweat, tears,
00:08:22 --> 00:08:25 but so much fun building something from scratch
00:08:25 --> 00:08:29 and doing that in the nicest possible way with
00:08:29 --> 00:08:33 a small, largely unknown UK PLC. and going out
00:08:33 --> 00:08:37 there and doing it well was enormously rewarding.
00:08:37 --> 00:08:40 And yeah, I learned an incredible amount. And
00:08:40 --> 00:08:44 I would say a few things have stayed with me.
00:08:44 --> 00:08:47 So I'd say the first one, the value of partners.
00:08:47 --> 00:08:51 So our big four relationships have been able
00:08:51 --> 00:08:54 to get us close to clients that we would never
00:08:54 --> 00:08:56 have been able to kind of reach on our own when
00:08:56 --> 00:08:59 we first landed in the US. And the power of those
00:08:59 --> 00:09:03 partners and the power that they can, it's not
00:09:03 --> 00:09:05 just the power, I think it's like the growth
00:09:05 --> 00:09:09 that they can enable for any company, as an organization,
00:09:09 --> 00:09:12 as a CEO, you can't be reliant on just direct
00:09:12 --> 00:09:16 sales, like use your ecosystem around you. And
00:09:16 --> 00:09:19 I think the second thing is And I think that
00:09:19 --> 00:09:22 goes back to what has always attracted me about
00:09:22 --> 00:09:25 aptitude, and that's making sure that you're
00:09:25 --> 00:09:27 listening to the customers, the market, making
00:09:27 --> 00:09:29 sure that you're building products that meet
00:09:29 --> 00:09:32 the needs of the market. And I think that the
00:09:32 --> 00:09:36 third is the pace, right? The US market moves
00:09:36 --> 00:09:40 faster than anywhere else, and it leads. and
00:09:40 --> 00:09:44 what happens there then kind of shows up everywhere
00:09:44 --> 00:09:48 else kind of 18 months later. So being really
00:09:48 --> 00:09:54 close to that market really helps. with product
00:09:54 --> 00:09:57 development and obviously innovation in terms
00:09:57 --> 00:10:00 of product development that then obviously translates
00:10:00 --> 00:10:02 into what we deliver and what our customers can
00:10:02 --> 00:10:05 then benefit from. So yeah, great experience.
00:10:06 --> 00:10:10 Loved every minute of it and learned so much
00:10:10 --> 00:10:13 to help me in my CEO role. That's amazing to
00:10:13 --> 00:10:16 hear, especially when you said I just came with
00:10:16 --> 00:10:19 a suitcase and had to get to work. Like curious
00:10:19 --> 00:10:23 to hear how you see the CFO role change just
00:10:23 --> 00:10:26 in that decade? Because I remember starting my
00:10:26 --> 00:10:29 career in accounting and finance and the CFOs
00:10:29 --> 00:10:31 was not what was not expected the same thing
00:10:31 --> 00:10:35 that the CFOs are, you know, expected today,
00:10:35 --> 00:10:39 especially how, you know, they accelerated like
00:10:39 --> 00:10:42 the pace of change in the office of the CFO.
00:10:42 --> 00:10:45 So what would you say are some of the pressures
00:10:45 --> 00:10:48 that you see from the finance leaders you're
00:10:48 --> 00:10:52 now listening to? Yeah, I think Yeah, totally
00:10:52 --> 00:10:55 agree with you. I think what the CFO was expected
00:10:55 --> 00:10:59 to do maybe, you know, 10, 20 years ago is very
00:10:59 --> 00:11:01 different to what they're expected to do now.
00:11:02 --> 00:11:06 I think long gone are the days where they are
00:11:06 --> 00:11:09 expected to be the, or allowed to be just kind
00:11:09 --> 00:11:12 of the historian, kind of the custodian of the
00:11:12 --> 00:11:15 data, where they're allowed to just kind of close
00:11:15 --> 00:11:19 the books on a monthly basis. basically, yeah,
00:11:19 --> 00:11:22 automate accounting, but that that those days
00:11:22 --> 00:11:24 are gone, I think the direction of travel isn't
00:11:24 --> 00:11:28 new CFOs providing or being that historian, they
00:11:28 --> 00:11:32 are very quickly moving towards needing to be
00:11:32 --> 00:11:34 that co pilot and having that co pilot relationship
00:11:34 --> 00:11:40 with their CEO. And I think what we've seen that,
00:11:40 --> 00:11:42 that transformation, that kind of change in role
00:11:42 --> 00:11:47 happened over the last five years, but the speed
00:11:47 --> 00:11:51 of change, has accelerated and what's changed
00:11:51 --> 00:11:56 I think is the clock. I think AI has removed
00:11:56 --> 00:12:00 the luxury of time. I think AI has definitely
00:12:00 --> 00:12:03 increased the pressure that boards are placing
00:12:03 --> 00:12:05 on the wider business because they want to see
00:12:05 --> 00:12:08 scenarios, modern forecasts in the moment, not
00:12:08 --> 00:12:10 in the pack, the board pack kind of next month.
00:12:11 --> 00:12:13 And I think quarterly rhythms are disappearing.
00:12:14 --> 00:12:18 I think now expectations need to be set in weeks,
00:12:18 --> 00:12:22 if not days. And there's a growing, growing push
00:12:22 --> 00:12:26 for a continuous close or even zero day, day
00:12:26 --> 00:12:29 close. And I think set against that, if your
00:12:29 --> 00:12:32 finance function is taking 15 days to close with
00:12:32 --> 00:12:36 complex reconciliations, manual processes, I
00:12:36 --> 00:12:38 think that ends up being quite a drag on a business.
00:12:38 --> 00:12:41 And that, again, doesn't go back to the team
00:12:41 --> 00:12:45 not doing a good job. I think the challenge that
00:12:45 --> 00:12:48 organizations are finding is that the architecture
00:12:48 --> 00:12:52 that has kind of underpinned finance teams for
00:12:52 --> 00:12:58 so long basically won't enable them to go faster.
00:12:59 --> 00:13:02 And I think lots of organizations are seeing
00:13:02 --> 00:13:07 that traditional ERPs can't get them to that
00:13:07 --> 00:13:11 kind of co -pilot. pilot status. And I think
00:13:11 --> 00:13:14 that pressure is becoming real across every sector,
00:13:15 --> 00:13:18 every region, across every CFO office that we're
00:13:18 --> 00:13:20 talking to and that our partners are talking
00:13:20 --> 00:13:23 to. So how do you feel about that? You know,
00:13:23 --> 00:13:27 you being a CEO, what are now your expectations
00:13:27 --> 00:13:30 from your own CFO, right? Like, what do you now
00:13:30 --> 00:13:33 feel like, yeah, as a CEO, I'm going through
00:13:33 --> 00:13:36 this, so I'm expecting my CFO to do? like what
00:13:36 --> 00:13:40 would you say is that for you? Yeah, so I would
00:13:40 --> 00:13:47 say that I want my CFO to look at the systems
00:13:47 --> 00:13:53 that support the function. I want the CFO to,
00:13:53 --> 00:13:56 we've all seen the SAS apocalypse. happened over
00:13:56 --> 00:13:59 the last kind of six to 12 months. I think there's
00:13:59 --> 00:14:02 a realisation that the pace of technology is
00:14:02 --> 00:14:04 changing much faster than anyone has ever seen.
00:14:05 --> 00:14:07 And I think what I would be saying to my CFO
00:14:07 --> 00:14:10 is just because you have implemented a traditional
00:14:10 --> 00:14:15 set of technologies in the past, looking at how
00:14:15 --> 00:14:19 AI is disrupting what organisations are needing
00:14:19 --> 00:14:23 to do, I'd encourage the CFOs to think incredibly
00:14:23 --> 00:14:26 differently about how and what they're going
00:14:26 --> 00:14:29 to implement to underpin their finance architecture
00:14:29 --> 00:14:32 to be able to drive real -time information to
00:14:32 --> 00:14:36 enable a continuous close and to enable a real
00:14:36 --> 00:14:39 -time P &L that the CFO and the CEO can then
00:14:39 --> 00:14:42 collaboratively work on and use that information,
00:14:42 --> 00:14:46 current information. to then drive the business
00:14:46 --> 00:14:50 forwards. So I think, yeah, the pressure is on,
00:14:50 --> 00:14:52 I think also not just for the CFOs, but the CEOs
00:14:52 --> 00:14:56 to encourage their CFOs to think very, very differently.
00:14:58 --> 00:15:00 Okay. And what would you say is the most common
00:15:00 --> 00:15:04 misalignment you see between a CEO and their
00:15:04 --> 00:15:09 CFO or the finance function? Yeah, good question.
00:15:09 --> 00:15:12 I would say it's... I would say it's usually
00:15:12 --> 00:15:17 not ambition, right? I think both sides I think
00:15:17 --> 00:15:20 typically want the same thing and that's the
00:15:20 --> 00:15:25 CEO is asking the questions and the CFO wants
00:15:25 --> 00:15:28 to be able to answer those questions instantaneously.
00:15:28 --> 00:15:30 But the challenge, the misalignment there right
00:15:30 --> 00:15:34 now is that the CFO can't answer it because the
00:15:34 --> 00:15:37 systems that underpin the finance team can't
00:15:37 --> 00:15:39 support that. And I think what you typically
00:15:39 --> 00:15:42 see right now within a finance architecture.
00:15:42 --> 00:15:45 And obviously I'm out speaking to the controllers,
00:15:45 --> 00:15:48 chief Catholic officers, CFOs all the time. And,
00:15:48 --> 00:15:49 you know, the common challenge that they have
00:15:49 --> 00:15:55 is that the data is batched, it's summarized.
00:15:56 --> 00:15:58 So when someone goes looking for the detail,
00:15:59 --> 00:16:01 you know... it either takes a long time to do
00:16:01 --> 00:16:04 or all the details gone. And then obviously then
00:16:04 --> 00:16:06 you've got the added pressure of AI. So if you
00:16:06 --> 00:16:10 put AI, sorry, I can't talk, but put AI on top
00:16:10 --> 00:16:13 of that and you end up getting half an answer
00:16:13 --> 00:16:16 and in finance, half an answer is worse than
00:16:16 --> 00:16:19 none, right? Because somebody still has to sign
00:16:19 --> 00:16:21 it. And what the business actually needs is numbers
00:16:21 --> 00:16:23 that you can defend to the board and the ability
00:16:23 --> 00:16:26 to spot something odd kind of. while there's
00:16:26 --> 00:16:29 actually still time to be able to fix it, not
00:16:29 --> 00:16:32 weeks later. And again, it's not about how hard
00:16:32 --> 00:16:34 the team is working, it's about what they're
00:16:34 --> 00:16:37 working on. So I think for me, the misalignment
00:16:37 --> 00:16:40 is the systems that underpin finance to be able
00:16:40 --> 00:16:45 to mobilize and enable CFOs to be able to support
00:16:45 --> 00:16:48 their shared ambitions because I do think there's
00:16:48 --> 00:16:50 great alignment. there in most organizations
00:16:50 --> 00:16:53 that we're talking to. And like how you said,
00:16:53 --> 00:16:55 we have the same ambitions because I've yet to
00:16:55 --> 00:16:57 meet a CFO who doesn't want to be able to answer
00:16:57 --> 00:17:02 those questions. But definitely at the foundation,
00:17:02 --> 00:17:06 it is hard to answer those questions in a timely
00:17:06 --> 00:17:10 manner. So would you say that the zero -day close
00:17:10 --> 00:17:13 is actually a reality? Because I still have a
00:17:13 --> 00:17:16 lot of CFOs and controllers that I like. Is it
00:17:16 --> 00:17:19 even possible to have a zero -day close? So I'm
00:17:19 --> 00:17:21 pretty sure, but I don't know what will be a
00:17:21 --> 00:17:25 figure. But I'm curious to hear, maybe it's just
00:17:25 --> 00:17:28 1 % that have a zero -day close. Is it a reality,
00:17:28 --> 00:17:31 first, before we dive into how we make it a reality?
00:17:31 --> 00:17:36 Yeah, of course. So I think it can be a reality.
00:17:36 --> 00:17:40 I think the number of organisations that have
00:17:40 --> 00:17:43 taken that leap and implemented finance systems
00:17:43 --> 00:17:48 that enable that reality are limited right now.
00:17:49 --> 00:17:51 We're working with a number of organisations
00:17:51 --> 00:17:56 where we have enabled a real -time P &L and they're
00:17:56 --> 00:17:59 struggling to find other organisations within
00:17:59 --> 00:18:03 their peer group who have achieved the same.
00:18:04 --> 00:18:06 And their biggest challenge now is not compliance.
00:18:06 --> 00:18:11 It's not automation. It's not having, you know,
00:18:11 --> 00:18:14 poor kind of reconciliations. All of that's fixed.
00:18:14 --> 00:18:18 Their challenge now is how do they actually operationalize
00:18:18 --> 00:18:21 that information to be able to serve their wider
00:18:21 --> 00:18:25 business and actually monetize, you know, the
00:18:25 --> 00:18:28 data. will use the data to monetize different
00:18:28 --> 00:18:32 services, launch different products to drive
00:18:32 --> 00:18:35 their business forwards. But yeah, it is a reality
00:18:35 --> 00:18:40 if a CFO and CEO are aligned on the fact that
00:18:40 --> 00:18:42 they need a system change and that they can't.
00:18:42 --> 00:18:45 reimplement or implement a technology that's,
00:18:45 --> 00:18:48 you know, 10 to 15 years old, you know, technology
00:18:48 --> 00:18:51 has moved on leaps and bounds. And I like how
00:18:51 --> 00:18:54 you said, like, once you have that zero day close,
00:18:54 --> 00:18:56 you can then move on to do all those other things
00:18:56 --> 00:18:58 that will help the rest of your business. But
00:18:58 --> 00:19:01 so many of us are tied into that first step.
00:19:01 --> 00:19:04 that there is only so much capacity when it's
00:19:04 --> 00:19:08 time to do other stuff. So curious to hear, since
00:19:08 --> 00:19:12 you work with CFOs who are facing down the next
00:19:12 --> 00:19:16 ERP transformation, it is a huge undertaking.
00:19:17 --> 00:19:20 So how do you guide them through that process?
00:19:20 --> 00:19:23 Whether it's getting the right alignment, finding
00:19:23 --> 00:19:25 the right tool, making sure the right tool is
00:19:25 --> 00:19:27 implemented the right way, because that's another
00:19:27 --> 00:19:32 hill as well. Yeah, yeah. I think, again, I think
00:19:32 --> 00:19:37 it's looking at how you kind of move away from
00:19:38 --> 00:19:40 what you've been comfortable with before. So
00:19:40 --> 00:19:42 I think, look, historically, there's been three
00:19:42 --> 00:19:46 choices out in the market. And those ERP systems
00:19:46 --> 00:19:49 have enabled organizations to kind of run their
00:19:49 --> 00:19:53 finance processes, their operations through it.
00:19:53 --> 00:19:54 And there's been a choice of three. You pick
00:19:54 --> 00:19:57 one, you crack on, and that's it. that the world
00:19:57 --> 00:20:00 has moved on, right? Like people need to have
00:20:00 --> 00:20:02 real time information and those traditionally
00:20:02 --> 00:20:06 RPs are, you know, are not going to be retrofitted
00:20:06 --> 00:20:11 for the AI era. And, you know, we've seen organizations
00:20:11 --> 00:20:14 spend millions and several years on transformations
00:20:14 --> 00:20:19 that have either failed or products or on products
00:20:19 --> 00:20:21 that, you know, kind of, you know, that weren't
00:20:21 --> 00:20:24 designed or never right for them. And that's
00:20:24 --> 00:20:27 the experience I think most CFOs have. are currently
00:20:27 --> 00:20:32 drawing on. So I think the caution makes complete
00:20:32 --> 00:20:36 sense. I was talking to a CFO a couple of days
00:20:36 --> 00:20:41 ago who was very open about the fact that they
00:20:41 --> 00:20:45 had upgraded their general ledger and they had
00:20:45 --> 00:20:49 purely upgraded their general ledger to take
00:20:49 --> 00:20:52 risk off the table. They'd spent millions upon
00:20:52 --> 00:20:55 millions doing it, years of the team's time.
00:20:55 --> 00:20:59 And his own assessment was that the finance function
00:20:59 --> 00:21:02 was, after all of that effort and spend, was
00:21:02 --> 00:21:05 no better off than when they started. That's
00:21:05 --> 00:21:09 a lot of money to stand still. And I don't think
00:21:09 --> 00:21:12 that that level of spend, that time, that effort
00:21:12 --> 00:21:16 to not move the dial and progress your business
00:21:16 --> 00:21:20 is something that CFOs can do anymore. But I
00:21:20 --> 00:21:24 think really positively they have been in that
00:21:24 --> 00:21:26 position because there haven't been solutions
00:21:26 --> 00:21:29 on the market that have enabled them to do something
00:21:29 --> 00:21:32 different. So I say my advice is pretty blunt,
00:21:32 --> 00:21:35 right? I would say don't buy legacy technology.
00:21:36 --> 00:21:40 Be brave and look at what else is out on the
00:21:40 --> 00:21:45 market because that's changed. And I don't think
00:21:45 --> 00:21:50 many CFOs have realized that. So again, you don't
00:21:50 --> 00:21:54 have to do it all at once also. I think there's
00:21:54 --> 00:21:58 a misconception that these finance transformation
00:21:58 --> 00:22:03 programs also have to be big bang. As an example,
00:22:04 --> 00:22:06 don't touch your general ledger. Extend the life
00:22:06 --> 00:22:08 of the investment that you've made, especially
00:22:08 --> 00:22:10 if the CFO that I've just spoken about has spent
00:22:10 --> 00:22:12 the last five years implementing it and spent
00:22:12 --> 00:22:15 hundreds of millions of dollars on it. Leave
00:22:15 --> 00:22:17 your general ledger where it is. It's designed
00:22:17 --> 00:22:20 to, it's meant to be light and it's meant to
00:22:20 --> 00:22:23 just literally be your exact management regulatory
00:22:23 --> 00:22:27 reporting level. What I would say is bring in
00:22:27 --> 00:22:29 a market -leading sub -ledger underneath it.
00:22:29 --> 00:22:32 because that's where you hold all of the complexity,
00:22:33 --> 00:22:34 that's where you hold all of your accounting
00:22:34 --> 00:22:36 logic, and that's where you hold all of your
00:22:36 --> 00:22:40 real -time information. So again, I think there
00:22:40 --> 00:22:43 are lots of different options out there for the
00:22:43 --> 00:22:46 CFO, and I think the other thing just to add
00:22:46 --> 00:22:53 to that that I would say is be careful when...
00:22:53 --> 00:22:55 You know, you're looking at technology where
00:22:55 --> 00:22:59 AI is kind of added on on top of old architecture.
00:22:59 --> 00:23:02 I think what we're seeing in the market is that
00:23:02 --> 00:23:06 by implementing old tech with kind of embedded
00:23:06 --> 00:23:10 AI in it, I don't think you actually fix many
00:23:10 --> 00:23:12 things. I think you just make the mess bigger
00:23:12 --> 00:23:15 and faster and considerably more more expensive.
00:23:16 --> 00:23:19 So, again, I would, yeah, there are lots of different
00:23:19 --> 00:23:21 technologies out there, not just aptitude software.
00:23:22 --> 00:23:26 So I would go out and have a look at the new
00:23:26 --> 00:23:29 kids on the block to be able to support your
00:23:29 --> 00:23:33 finance process. Wow. You touched on so many
00:23:33 --> 00:23:35 good points there. I just want to go back to
00:23:35 --> 00:23:39 when you talked about how legacy ERPs cannot
00:23:39 --> 00:23:44 really help you in what AI is now requiring of
00:23:44 --> 00:23:46 the finance function. Can you please explain
00:23:46 --> 00:23:49 a little bit more and also from some of our listeners
00:23:49 --> 00:23:52 not understanding fully what an ERP supposed
00:23:52 --> 00:23:54 to do in the first place? Yeah, so look, you've
00:23:54 --> 00:23:59 got an ERP that does a couple of things. So traditionally
00:23:59 --> 00:24:02 you think of an ERP that supports your kind of
00:24:02 --> 00:24:04 operational part of your business. So your HR,
00:24:05 --> 00:24:08 your procurement, your supply chain, really important,
00:24:08 --> 00:24:12 you know. pieces of the business, but not necessarily
00:24:12 --> 00:24:15 pieces, components of the business that will
00:24:15 --> 00:24:18 drive or change your strategic direction. That's
00:24:18 --> 00:24:20 on one side. And then on the other side, you
00:24:20 --> 00:24:23 have your finance ERP. So you've got your general
00:24:23 --> 00:24:26 ledger, you've got your AP, you've got your AR,
00:24:26 --> 00:24:30 and you've got fixed assets just as some of the,
00:24:31 --> 00:24:33 to give examples of some of the modules that
00:24:33 --> 00:24:38 you see within some of your finance ERP. the
00:24:38 --> 00:24:43 finance component of the ERP. So that is an ERP.
00:24:44 --> 00:24:46 And that, as I said earlier, kind of typically
00:24:46 --> 00:24:48 there are three vendors out in the market, I'm
00:24:48 --> 00:24:50 sure everyone knows who they are, who have kind
00:24:50 --> 00:24:53 of captured that market and organizations have
00:24:53 --> 00:24:55 traditionally just run their business through
00:24:55 --> 00:24:58 it. But if you look at the finance ERP component,
00:24:58 --> 00:25:00 if you're looking at one of the big three, you
00:25:00 --> 00:25:03 know, legacy technology, technology that's been
00:25:03 --> 00:25:08 around for 10, 15 years, maybe more, very rigid,
00:25:08 --> 00:25:11 so, you know, very difficult to kind of evolve,
00:25:11 --> 00:25:14 to amend in line with, you know, launching of
00:25:14 --> 00:25:17 new products or going into new countries or adding
00:25:17 --> 00:25:21 different accounting rules. In addition to that,
00:25:21 --> 00:25:25 they're typically batched, so they process. data
00:25:25 --> 00:25:29 in batches versus real time and they typically
00:25:29 --> 00:25:32 don't process high transaction volume. So you
00:25:32 --> 00:25:35 are and you have kind of aggregated information.
00:25:35 --> 00:25:39 When it comes to AI, they are not AI native.
00:25:39 --> 00:25:41 Obviously, they've been around for a long time,
00:25:41 --> 00:25:44 so they haven't been built up from the ground
00:25:44 --> 00:25:47 up with AI in mind because AI didn't really exist
00:25:47 --> 00:25:51 10, 15 years ago. So what they're doing is they're
00:25:51 --> 00:25:55 embedding AI technology into their old technology.
00:25:56 --> 00:25:59 And that AI technology will then be sat within
00:25:59 --> 00:26:03 those products for the next three to five to
00:26:03 --> 00:26:06 10 years. And obviously we've seen the speed
00:26:06 --> 00:26:10 and the pace of change. And therefore what we're
00:26:10 --> 00:26:14 seeing in the market is a a new set of finance
00:26:14 --> 00:26:17 ERP vendors coming to the market that are AI
00:26:17 --> 00:26:21 native. And what that means is that they can
00:26:21 --> 00:26:24 plug and play with any AI technology and therefore
00:26:24 --> 00:26:28 you're not tied to one particular AI vendor as
00:26:28 --> 00:26:31 an example. And you need that optionality based
00:26:31 --> 00:26:34 on obviously the change of pace that we're seeing.
00:26:34 --> 00:26:37 Wow. And so what would you say are some of the
00:26:37 --> 00:26:41 things that an AI native ERP can do? like just
00:26:41 --> 00:26:45 to give people an idea of, hey, this would be
00:26:45 --> 00:26:49 basic if this wasn't an AI native ERP versus
00:26:49 --> 00:26:52 you trying to retrofit into the legacy ERP you
00:26:52 --> 00:26:55 have. Yeah. So look, I think the new set of finance
00:26:55 --> 00:26:59 ERPs can do a lot of... A lot of great things.
00:26:59 --> 00:27:04 So I think they, number one, they remove the
00:27:04 --> 00:27:09 elongated, costly, expensive project implementation
00:27:09 --> 00:27:13 timelines. So I think if you look at traditional
00:27:13 --> 00:27:16 ERP, finance ERP, you're probably looking at
00:27:16 --> 00:27:18 two to three to five years, tens, if not hundreds
00:27:18 --> 00:27:20 of millions of dollars to implement. The way
00:27:20 --> 00:27:24 in which these vendors have set themselves up
00:27:24 --> 00:27:28 is that they have built these technologies with
00:27:28 --> 00:27:32 a set of predefined templates, set of assets
00:27:32 --> 00:27:34 that help to kind of accelerate the implementation
00:27:34 --> 00:27:38 time. And also they have brought in a lot of
00:27:38 --> 00:27:42 use of AI to automate configurations. So again,
00:27:42 --> 00:27:45 I think that's a big tick. Secondly, it gives
00:27:45 --> 00:27:49 you that optionality. So you're not tied to a
00:27:49 --> 00:27:53 particular. AI tech, so if you're using Chachapi
00:27:53 --> 00:27:57 -T, maybe now, but you're then gonna go to OpenAI
00:27:57 --> 00:28:01 and utilize different, I guess, capabilities
00:28:01 --> 00:28:05 from different AI vendors. They provide the kind
00:28:05 --> 00:28:09 of standard APIs that you can plug in and play.
00:28:09 --> 00:28:11 So again, it gives you that flexibility. And
00:28:11 --> 00:28:13 then obviously going back to your original, or
00:28:13 --> 00:28:16 one of your original questions was, is a continuous
00:28:16 --> 00:28:21 close, real -time close, zero -day close possible,
00:28:22 --> 00:28:24 the way in which these vendors are setting their
00:28:24 --> 00:28:26 systems up to process hundreds of millions of
00:28:26 --> 00:28:30 journal lines, to stream information, to stream
00:28:30 --> 00:28:35 data, they are making sure that their systems
00:28:35 --> 00:28:38 and solutions support that zero -day close. They
00:28:38 --> 00:28:42 are making it possible. So yeah, I think it's...
00:28:42 --> 00:28:45 Yeah, an important shift and change that we're
00:28:45 --> 00:28:48 seeing in the market. And I think more CFO should
00:28:48 --> 00:28:52 go out and evaluate those vendors. And these
00:28:52 --> 00:28:54 are all amazing. I mean, just to think that what
00:28:54 --> 00:28:56 used to take three, five years you can do within
00:28:56 --> 00:29:00 a year of implementation is amazing. And then
00:29:00 --> 00:29:03 you now can see how every line that comes through
00:29:03 --> 00:29:07 an expense report can be on the financial statement
00:29:07 --> 00:29:09 instead of waiting to be batched and approved.
00:29:10 --> 00:29:12 I think it's It's pretty amazing and exciting
00:29:12 --> 00:29:15 at the same time, but also scary, right? For
00:29:15 --> 00:29:18 some people it's like, okay, I'm not sure, am
00:29:18 --> 00:29:21 I letting go of something? And then opening myself
00:29:21 --> 00:29:24 to more risks. So I'm curious to hear, how do
00:29:24 --> 00:29:28 you think AI has impacted those strategic partnerships
00:29:28 --> 00:29:31 between CFOs and their CEOs, like when they're
00:29:31 --> 00:29:35 having those conversations around AI? Let's take
00:29:35 --> 00:29:38 a quick break so I can tell you more about FineApps.
00:29:38 --> 00:29:41 FineApps is an AI native finance ERP that runs
00:29:41 --> 00:29:44 in real time, which means it's a new product
00:29:44 --> 00:29:46 that moves beyond the limitation of a traditional
00:29:46 --> 00:29:49 ERP general ledger, which takes weeks to close
00:29:49 --> 00:29:51 the books and can only report numbers from the
00:29:51 --> 00:29:54 past. FineApps is a super ledger, a unified system
00:29:54 --> 00:29:57 of four detail summary and reporting that captures
00:29:57 --> 00:30:00 every financial event in detail. It is not a
00:30:00 --> 00:30:03 whole product with AI bolted on top. It is truly
00:30:03 --> 00:30:06 AI native. They have guardrails for agents who
00:30:06 --> 00:30:09 run inside the system and produce numbers that
00:30:09 --> 00:30:12 are traced back to the event. So financing might
00:30:12 --> 00:30:14 always audit ready. If you want to learn more
00:30:14 --> 00:30:17 about the solution, I do encourage you to visit
00:30:17 --> 00:30:22 fineapps .app. It is F -Y -N -A -P -S -E. I will
00:30:22 --> 00:30:25 drop the link in the show notes. Yeah. So I look,
00:30:25 --> 00:30:28 I think it's. I think it's raised the stakes
00:30:28 --> 00:30:33 for both of them. And we actually, we funded
00:30:33 --> 00:30:37 some research on this as part of our autonomous
00:30:37 --> 00:30:42 finance survey. And I think the numbers were,
00:30:42 --> 00:30:46 I think it was something like 87 % of CFOs, I
00:30:46 --> 00:30:52 think, said that AI will be important to their
00:30:52 --> 00:30:56 finance operations this year. And then I think
00:30:56 --> 00:31:01 it was something like 7%, 8 % of them were only
00:31:01 --> 00:31:04 actually able to point to kind of any measurable
00:31:04 --> 00:31:10 return. And I think that's quite a stark stack.
00:31:10 --> 00:31:13 87 wants it, but not even 10 % actually have
00:31:13 --> 00:31:18 it. So I think, you know, how does that kind
00:31:18 --> 00:31:23 of change the CFO CEO partnership? And I think
00:31:23 --> 00:31:27 it goes back to, you know, the systems that underpin
00:31:27 --> 00:31:31 it. So I think the CFO ends up being caught between,
00:31:31 --> 00:31:34 you know, a CEO asking for kind of real time
00:31:34 --> 00:31:37 answers, and again, back to the system, right,
00:31:37 --> 00:31:39 and the system that actually can't produce them.
00:31:40 --> 00:31:42 But I think, though, what's really important
00:31:42 --> 00:31:46 to that is that it strengthens, I think the AI
00:31:46 --> 00:31:49 topic in general, right, strengthens that partnership
00:31:49 --> 00:31:53 between the CFO and the CEO. And I think, you
00:31:53 --> 00:31:55 know, making sure that they are working extremely
00:31:55 --> 00:31:59 close together to make sure that the finance
00:31:59 --> 00:32:03 function is set up to be able to support that
00:32:03 --> 00:32:07 ambition is is key core core fundamental. So
00:32:07 --> 00:32:09 I think it brings them closer together because
00:32:09 --> 00:32:12 the stresses and the strains and the asks become
00:32:12 --> 00:32:19 louder. Now, about the 87 % of CFOs wants it,
00:32:19 --> 00:32:23 but only 7 % can show ROI. What would you say
00:32:23 --> 00:32:25 are three things that CFOs should understand
00:32:25 --> 00:32:28 about handling the pressure of delivering an
00:32:28 --> 00:32:32 AI strategy that demonstrate ROI, like an actual
00:32:32 --> 00:32:34 return on investment? Not just saying I just
00:32:34 --> 00:32:37 checked the box, but I'm actually getting something
00:32:37 --> 00:32:42 out of it. Yeah, I think... So what should, yeah,
00:32:42 --> 00:32:44 I guess three things CFO should understand about
00:32:44 --> 00:32:48 delivering that ROI. I would say, first of all,
00:32:48 --> 00:32:52 what I think it's the data, well, I would say
00:32:52 --> 00:32:55 that data is key core fundamental, right? So
00:32:55 --> 00:32:58 making sure that you've got... data in one place
00:32:58 --> 00:33:01 that's highly granular, that's books record quality,
00:33:02 --> 00:33:05 that's controlled and governed is important because
00:33:05 --> 00:33:07 I think it's the data, not the model. I think
00:33:07 --> 00:33:09 the models are absolutely extraordinary, right?
00:33:09 --> 00:33:11 But what's failing underneath them is that the
00:33:11 --> 00:33:14 data that you see in these finance functions,
00:33:15 --> 00:33:18 it's either siloed or it's batched and summarized
00:33:18 --> 00:33:22 before AI has even ever. seen it. And I think
00:33:22 --> 00:33:28 that that's a big kind of undertaking for CFOs
00:33:28 --> 00:33:33 and CEOs to be working through. So I think that's
00:33:33 --> 00:33:36 something that you've got to get right. And I
00:33:36 --> 00:33:39 think secondly, if you can't trace it, you can't
00:33:39 --> 00:33:43 defend it, you can't act on it. and if you can't
00:33:43 --> 00:33:45 act on it, then there's absolutely no return.
00:33:45 --> 00:33:48 So I think that's the first point I want to make.
00:33:48 --> 00:33:50 I think in addition to that, I think it's not
00:33:50 --> 00:33:53 just the data. Again, right, you need as, I'll
00:33:53 --> 00:33:55 probably sound like a stock record, but you've
00:33:55 --> 00:33:57 got to have the right technology underneath it
00:33:57 --> 00:34:01 to support it too. And I think again, going back
00:34:01 --> 00:34:03 to... really understanding the difference between
00:34:03 --> 00:34:07 what an AI native technology solution is and
00:34:07 --> 00:34:10 one that's AI enabled is key core fundamental
00:34:10 --> 00:34:13 because you don't want to be stuck with one particular
00:34:13 --> 00:34:17 AI technology that then changes their commercial
00:34:17 --> 00:34:22 model and then the spend that you have to increase
00:34:22 --> 00:34:24 to be able to keep up with how users are using
00:34:24 --> 00:34:26 it. Again, you want that option to be able to
00:34:26 --> 00:34:28 kind of flex in and out. And then I think the
00:34:28 --> 00:34:31 third point would be making sure that you kind
00:34:31 --> 00:34:34 of keep the human in the loop. I think, you know,
00:34:34 --> 00:34:36 AI, I think there's a misconception. I think
00:34:36 --> 00:34:39 you hear lots of noise in the media at the moment
00:34:39 --> 00:34:42 about the fact that AI isn't, you know, it's
00:34:42 --> 00:34:46 here to kind of replace humans. In my view, AI
00:34:46 --> 00:34:49 isn't here to replace your team. You've got to
00:34:49 --> 00:34:52 trust what it surfaces, but you also then, in
00:34:52 --> 00:34:54 finance especially, right, you need someone who's
00:34:54 --> 00:34:57 checked it and will stand behind it. So, yeah,
00:34:57 --> 00:35:00 I think there's a lot that organizations get
00:35:00 --> 00:35:02 out of it, but I think you have to get the data
00:35:02 --> 00:35:05 right, get the technology right, and make sure
00:35:05 --> 00:35:08 that you keep humans in the process to make sure
00:35:08 --> 00:35:10 that you can realize the return on investment
00:35:10 --> 00:35:12 and measure it especially as well. Yeah. What
00:35:12 --> 00:35:14 would you say are some of the things that, like,
00:35:14 --> 00:35:18 what is the one thing CFOs struggle the most
00:35:18 --> 00:35:19 with? I know you mentioned getting your data
00:35:19 --> 00:35:21 right, making sure you have the right technology,
00:35:22 --> 00:35:24 making sure you are able to have the right...
00:35:24 --> 00:35:27 you know, the right human, also the right process
00:35:27 --> 00:35:29 to have the human in the loop. What would you
00:35:29 --> 00:35:32 say from your conversations is the number one
00:35:32 --> 00:35:35 thing that most CFOs struggle? I think it's the
00:35:35 --> 00:35:39 systems. I think it's technology enabling them
00:35:39 --> 00:35:44 to do what they need to do. Because, again, I
00:35:44 --> 00:35:46 don't think you can fix a data without fixing
00:35:46 --> 00:35:48 the system that holds it. And I think people
00:35:48 --> 00:35:52 try it. But they put kind of racks on top or
00:35:52 --> 00:35:56 a reporting layer. or they try and, in addition
00:35:56 --> 00:35:59 to that, kind of try and clean things up manually.
00:36:00 --> 00:36:02 But if your systems that you're using, whether
00:36:02 --> 00:36:06 or not it's for subledger, general ledger, FP
00:36:06 --> 00:36:10 &A, if it's not being fed by clean real -time
00:36:10 --> 00:36:14 information and you have a data hub, finance
00:36:14 --> 00:36:17 data hub that's holding information at a transactional
00:36:17 --> 00:36:21 level in the first place, Yeah, it's very, very
00:36:21 --> 00:36:26 difficult to support any kind of AI strategy
00:36:26 --> 00:36:31 as well. So for the CFO listings who are indeed
00:36:31 --> 00:36:34 struggling with the technology part like where
00:36:34 --> 00:36:38 should they begin? Because you know we hear a
00:36:38 --> 00:36:41 lot that data Like a lot of people I spoke to
00:36:41 --> 00:36:43 that okay your data, right? You actually one
00:36:43 --> 00:36:45 of the few people that said okay You probably
00:36:45 --> 00:36:48 need a better technology altogether that will
00:36:48 --> 00:36:50 help you with your data and help you with having
00:36:50 --> 00:36:53 the human Right? Some technology that helps you
00:36:53 --> 00:36:57 bring those three key elements together. So where
00:36:57 --> 00:37:00 would you say is, you know, what are one or two
00:37:00 --> 00:37:03 steps? Where should CFOs begin on that journey?
00:37:04 --> 00:37:08 Yeah. Look, I think before you select any vendor,
00:37:08 --> 00:37:13 I think you run through a checklist. I think
00:37:13 --> 00:37:15 these are some of the questions that now need
00:37:15 --> 00:37:18 to be asked. I think when you're talking to a
00:37:18 --> 00:37:20 vendor, I think you need to be talking to them
00:37:20 --> 00:37:23 about whether or not the AI, is it working on
00:37:23 --> 00:37:26 the transaction level data? Can you trace every
00:37:26 --> 00:37:29 number back to the transaction that's been generated?
00:37:30 --> 00:37:32 Going back to your close point, does your close
00:37:32 --> 00:37:36 or can the system allow you to run a closed process
00:37:36 --> 00:37:40 continuously? And making sure, especially if
00:37:40 --> 00:37:42 you're looking at some of the AI native solutions
00:37:42 --> 00:37:46 out there, does the governance live in the accounting
00:37:46 --> 00:37:48 engine itself? And do you get the same output
00:37:48 --> 00:37:51 for the same input every single time? I would
00:37:51 --> 00:37:53 say two other things I'd watch out for. Don't
00:37:53 --> 00:37:56 get locked into a vendor that insists that you
00:37:56 --> 00:37:58 use their agent or ties you to one model. Again,
00:37:58 --> 00:38:02 going back to the AI native point, AI is moving
00:38:02 --> 00:38:05 too fast. Technology is moving too fast to be
00:38:05 --> 00:38:08 locked in. And then I would also say prioritize
00:38:08 --> 00:38:11 what we describe as a kind of a glass box model
00:38:11 --> 00:38:14 where you can trace the lineage of every number
00:38:14 --> 00:38:17 the AI gives you. I think. you know, it's okay
00:38:17 --> 00:38:20 and no offense to the marketing teams out there.
00:38:20 --> 00:38:23 If marketing launch a promotional activity, a
00:38:23 --> 00:38:27 campaign, you know, if a campaign doesn't work
00:38:27 --> 00:38:31 as effectively as maybe the marketing team had
00:38:31 --> 00:38:34 hoped, I guess, you know, it's okay, not great,
00:38:35 --> 00:38:39 but okay. you go out with a number within finance,
00:38:39 --> 00:38:41 you go out to shareholders, your investors, the
00:38:41 --> 00:38:44 public markets with an incorrect number, you
00:38:44 --> 00:38:46 know, the consequences can be disastrous, right?
00:38:46 --> 00:38:50 So really thinking through has this vendor, you
00:38:50 --> 00:38:55 know, had the experience working with large publicly
00:38:55 --> 00:38:59 facing organizations that drive and demand the
00:38:59 --> 00:39:01 controls of other highly regulated industries
00:39:01 --> 00:39:04 is key core fundamental as well, because the
00:39:04 --> 00:39:09 consequences of not being able to prove that
00:39:09 --> 00:39:11 answer and make sure it's correct are extremely
00:39:11 --> 00:39:14 serious as every CFO listening knows all too
00:39:14 --> 00:39:18 well. Yeah, and I love your checklist and the
00:39:18 --> 00:39:21 question that resonated the most with me is we
00:39:21 --> 00:39:26 get the same output. for the right input, like
00:39:26 --> 00:39:29 that part. Curious to hear more about that, like,
00:39:29 --> 00:39:31 because it is, you know, different model will
00:39:31 --> 00:39:33 give you different things, but curious to hear,
00:39:33 --> 00:39:35 like, what, what actually goes in the background
00:39:35 --> 00:39:37 to make sure you, you actually get it. Cause
00:39:37 --> 00:39:39 for a human, for example, I know that one plus
00:39:39 --> 00:39:44 one equal two, right? I know it. If I know where
00:39:44 --> 00:39:46 the data comes from, I'm able to recalculate.
00:39:46 --> 00:39:50 If I use Excel, I'm able to retrace a formula.
00:39:50 --> 00:39:54 And sometimes AI feels like a black box. So curious
00:39:54 --> 00:39:57 to hear what maybe your solutions or what you've
00:39:57 --> 00:40:00 seen in the market or in your conversations have
00:40:00 --> 00:40:03 helped make sure that every time you are asking
00:40:03 --> 00:40:07 AI for this, you actually get the right result.
00:40:07 --> 00:40:09 Because you're right. Getting the wrong result
00:40:09 --> 00:40:12 can really put you in trouble in finance and
00:40:12 --> 00:40:17 accounting? Yeah, look, I think we've spent an
00:40:17 --> 00:40:20 awful lot of time, a great deal of time, you
00:40:20 --> 00:40:21 know, working with some of the largest, most
00:40:21 --> 00:40:23 complex organizations in the world, helping them
00:40:23 --> 00:40:27 with regulation, compliance, helping them with
00:40:27 --> 00:40:30 their subledger capabilities. And therefore,
00:40:30 --> 00:40:33 you know, when it comes to our software product,
00:40:33 --> 00:40:35 finance, you know, we've taken everything that
00:40:35 --> 00:40:38 we've learned through those finance transformation
00:40:38 --> 00:40:43 projects. and we have made sure that FineApps
00:40:43 --> 00:40:46 has those frameworks, those controls, the governance,
00:40:47 --> 00:40:51 the data lineage, the audit capabilities, and
00:40:51 --> 00:40:54 when it comes to our agents that work within
00:40:54 --> 00:40:58 it. that software product. We ensure that they
00:40:58 --> 00:41:02 obviously work in line with those governance
00:41:02 --> 00:41:05 structures and frameworks, but frameworks and
00:41:05 --> 00:41:08 governance structures that have been established.
00:41:09 --> 00:41:13 I guess are proven to have worked with, as I
00:41:13 --> 00:41:15 said, some of the most largest organizations
00:41:15 --> 00:41:20 in the world time and again. So I think for me,
00:41:20 --> 00:41:24 you know, would I recommend a CFO look at an
00:41:24 --> 00:41:27 AI native software vendor that spent the last
00:41:27 --> 00:41:29 two or three years in the market? No. But would
00:41:29 --> 00:41:32 I recommend that they look at an AI native solution
00:41:32 --> 00:41:34 to support their finance and accounting processes
00:41:34 --> 00:41:36 with a vendor that's been in the market for 30
00:41:36 --> 00:41:39 or 40 years and has done this many times before?
00:41:39 --> 00:41:43 then yes. But again, you've got to be very obviously
00:41:43 --> 00:41:46 careful within the finance realm in terms of
00:41:46 --> 00:41:49 how we use agents. within these software products.
00:41:50 --> 00:41:52 Let's talk about agents. I have one question.
00:41:53 --> 00:41:56 So if we were to talk a little bit more about
00:41:56 --> 00:42:01 agents. So obviously agent can do things, break
00:42:01 --> 00:42:03 things or things like that. Like what is the
00:42:03 --> 00:42:06 right setup? Like what is okay for an agent to
00:42:06 --> 00:42:09 do versus not okay for an agent to do for people
00:42:09 --> 00:42:12 just getting into agentic AI? Yeah, of course.
00:42:13 --> 00:42:16 Look, I think agents should be used for some
00:42:16 --> 00:42:19 of the more menial tasks, kind of tasks that
00:42:19 --> 00:42:23 I think humans can stop doing and start working
00:42:23 --> 00:42:26 on other interesting things. So, you know, basically
00:42:26 --> 00:42:31 looking for anomalies in the data that the system
00:42:31 --> 00:42:35 receives as an example, looking at how and supporting
00:42:35 --> 00:42:39 reconciliations, looking at automating manual
00:42:39 --> 00:42:43 tasks. So for me, I think agents should be used
00:42:43 --> 00:42:47 for those types of activities. in the initial
00:42:47 --> 00:42:52 phases and I think then the humans can then work
00:42:52 --> 00:42:55 on how do we use the data that we're generating
00:42:55 --> 00:42:58 if we are achieving a zero -day close and we
00:42:58 --> 00:43:01 actually are able to work on current data. How
00:43:01 --> 00:43:04 could FP &A, how can risk, how can marketing
00:43:04 --> 00:43:08 actually benefit from that? So I think initially,
00:43:08 --> 00:43:11 I think as you build trust in those agents, I
00:43:11 --> 00:43:14 think it's those, yeah, more kind of manual tasks
00:43:14 --> 00:43:17 as part of your process. Okay. And then as you
00:43:17 --> 00:43:20 graduate, like once you have the agents do the
00:43:20 --> 00:43:23 manual, like what is the next step? I think they
00:43:23 --> 00:43:25 can do lots of different things. I've worked
00:43:25 --> 00:43:30 with lots of big four organizations and they
00:43:30 --> 00:43:33 talk about the concept of organizations having
00:43:33 --> 00:43:37 a fully autonomous finance function where they
00:43:37 --> 00:43:40 have agents literally running their finance functions.
00:43:40 --> 00:43:44 You have controllers sitting in each of the entities
00:43:44 --> 00:43:47 that the controllers are agents. They talk to
00:43:47 --> 00:43:50 one another. They discuss. how to approach and
00:43:50 --> 00:43:54 how to address certain problems. And then they
00:43:54 --> 00:43:57 call upon the human, obviously when they hit
00:43:57 --> 00:44:00 a restriction or something that they need to
00:44:00 --> 00:44:02 obviously go to a human for a checkpoint as an
00:44:02 --> 00:44:06 example. So I think the use of agents can go
00:44:06 --> 00:44:10 broad and very wide, but where organizations
00:44:10 --> 00:44:13 are right now, organizations are still, I think,
00:44:13 --> 00:44:15 very focused on even trying to get the basics
00:44:15 --> 00:44:18 right, automating the finance processes. cleaning
00:44:18 --> 00:44:21 up the data, making sure that they can actually
00:44:21 --> 00:44:24 even get to a real time close by making changes
00:44:24 --> 00:44:27 to their upfront systems to make sure that they
00:44:27 --> 00:44:30 can support event level accounting. So I think
00:44:30 --> 00:44:33 moving from that to then having an autonomous
00:44:33 --> 00:44:35 finance function I think is, I'm not saying it's
00:44:35 --> 00:44:38 10 years away, but it's probably a long way away
00:44:38 --> 00:44:40 from where they are today. But yeah, I think
00:44:40 --> 00:44:43 it's going to be incredibly interesting to see
00:44:43 --> 00:44:47 the adoption and who moves fast and what the
00:44:47 --> 00:44:50 impact practice to the wider industry. And that's
00:44:50 --> 00:44:53 very, that's, that's very exciting for me. Because
00:44:53 --> 00:44:56 I remember when I started my, my accounting career,
00:44:56 --> 00:44:58 we're just trying to do a five day close. Like
00:44:58 --> 00:45:03 that was like, just five days. Can we close in
00:45:03 --> 00:45:07 five days? That was like the gold standard. And
00:45:07 --> 00:45:10 to see that now zero day close is like the goal.
00:45:10 --> 00:45:12 Like when somebody tells me they're closing one
00:45:12 --> 00:45:14 day, I'm like, let's get on the calendar. Let's
00:45:14 --> 00:45:19 meet. because it is so, it's super exciting.
00:45:19 --> 00:45:22 So curious to hear from your seat as a CEO, what
00:45:22 --> 00:45:26 may be something that now you see as a gold standard
00:45:26 --> 00:45:29 and probably a decade when you started Aptitude
00:45:29 --> 00:45:33 in North America, it was just like, eh, you know,
00:45:33 --> 00:45:35 I didn't see it that way. So curious to hear
00:45:35 --> 00:45:39 what's exciting for you right now. I think what
00:45:39 --> 00:45:43 is exciting is that we are seeing the pressure,
00:45:44 --> 00:45:47 like AI, I would say, we're seeing AI act as
00:45:47 --> 00:45:52 a compliance standard in terms of how organizations
00:45:52 --> 00:45:55 are feeling the pressure to make sure that they
00:45:55 --> 00:46:00 are utilizing AI effectively across their organization,
00:46:00 --> 00:46:03 starting with finance. And what I think is really
00:46:03 --> 00:46:05 exciting, and I would say this right, I'm the
00:46:05 --> 00:46:09 CEO of an AI native finance and accounting system.
00:46:10 --> 00:46:14 But I'm seeing CFOs acknowledge that the traditional
00:46:14 --> 00:46:17 ERPs are not going to be able to support them
00:46:17 --> 00:46:19 in this AI era. You know, for their time, right,
00:46:19 --> 00:46:21 they were absolutely extraordinary. But there
00:46:21 --> 00:46:26 is a shift taking place and there is a realization
00:46:26 --> 00:46:30 that... Organizations that aren't able to move
00:46:30 --> 00:46:32 in this direction aren't able to properly kind
00:46:32 --> 00:46:36 of swept the use of AI or have the data at their
00:46:36 --> 00:46:39 fingertips will be at a disadvantage because
00:46:39 --> 00:46:42 there are organizations out there who have recognized
00:46:42 --> 00:46:45 this and are in the process of implementing AI
00:46:45 --> 00:46:48 native finance solutions to be able to enable
00:46:48 --> 00:46:51 them to get ahead of the market. And those that
00:46:51 --> 00:46:54 don't make that change and that are slow to make
00:46:54 --> 00:46:58 that change will fall. further and further behind.
00:46:58 --> 00:47:01 So I think it's super exciting right now, not
00:47:01 --> 00:47:03 just as obviously as a finance and accounting
00:47:03 --> 00:47:07 software CEO, but actually to see what organizations
00:47:07 --> 00:47:09 and businesses can do and what they can achieve
00:47:09 --> 00:47:12 through having these capabilities internally
00:47:12 --> 00:47:15 and really exciting for their teams as well.
00:47:15 --> 00:47:17 You know, teams that have spent years kind of
00:47:17 --> 00:47:20 manually reconciling information, hand ticking
00:47:20 --> 00:47:23 and tying kind of charts of accounts. Yeah, finally
00:47:23 --> 00:47:26 are going to be able to actually work. of the
00:47:26 --> 00:47:29 exciting parts of the business. And I think that's,
00:47:29 --> 00:47:31 yeah, I think that's it. It's a super interesting
00:47:31 --> 00:47:34 place to be right now. Yeah, I cannot wait to
00:47:34 --> 00:47:37 be able to just go on vacation at the end of
00:47:37 --> 00:47:39 the month. Like that has been the biggest flex,
00:47:40 --> 00:47:42 like in being in accounting and finance, because
00:47:42 --> 00:47:45 you literally, like for decades, as long as I
00:47:45 --> 00:47:47 can remember, you literally structuring your
00:47:47 --> 00:47:52 time off your vacation around those you know,
00:47:52 --> 00:47:55 quarter end and month end and all these duties.
00:47:55 --> 00:47:59 So I'm really, really excited about that. I have
00:47:59 --> 00:48:01 one last question for you before we leave. What
00:48:01 --> 00:48:04 is your favorite thing to do outside of work?
00:48:05 --> 00:48:10 Well, as you can imagine, aptitude takes up an
00:48:10 --> 00:48:12 awful lot of my time. I'm very passionate about
00:48:12 --> 00:48:16 this business. I love this business. I believe
00:48:16 --> 00:48:20 deeply in what we're doing and what that could
00:48:20 --> 00:48:25 enable for the aptitude team. So therefore, what
00:48:25 --> 00:48:27 do I do outside of business when I have some
00:48:27 --> 00:48:30 time? It probably sounds very dull and boring,
00:48:31 --> 00:48:35 but I spend it with my family and my husband
00:48:35 --> 00:48:40 also. I have to mention him. But yeah, so family,
00:48:41 --> 00:48:43 friends, and in addition to that, I'm a firm
00:48:43 --> 00:48:49 believer in exercise, body and mind. So I very
00:48:49 --> 00:48:53 much like going to the gym, riding my bike, playing
00:48:53 --> 00:48:57 tennis, all of the above to make sure that...
00:48:57 --> 00:49:02 you know, I can sustain the energy that I need.
00:49:02 --> 00:49:06 So yeah, so yeah, I don't have any crazy hobbies,
00:49:06 --> 00:49:09 I'm afraid. Well, that's already good. Like right
00:49:09 --> 00:49:12 now, my hobby is being able to take a nap on
00:49:12 --> 00:49:16 the weekend. I didn't know at this age, I would
00:49:16 --> 00:49:19 be looking forward to take a nap. But it's just
00:49:19 --> 00:49:23 been a thing for me. Good thing. Good thing.
00:49:23 --> 00:49:28 Yes. So thank you so, so much, Alex, for being
00:49:28 --> 00:49:31 on the show here. If anyone is listening and
00:49:31 --> 00:49:34 wants to follow your work and learn more about
00:49:34 --> 00:49:37 your work, find apps and yourself, where should
00:49:37 --> 00:49:40 they go? Yeah, of course. So Aptitude Software
00:49:40 --> 00:49:45 is the organization that I represent. So, yeah,
00:49:45 --> 00:49:50 LinkedIn, to me, or for our website, which is
00:49:50 --> 00:49:55 obviously www .aptitudesoftware. And yeah, we'd
00:49:55 --> 00:50:00 be very much looking forward to hearing from
00:50:00 --> 00:50:03 you all. Thank you so much. And that's it for
00:50:03 --> 00:50:05 today's episode. If you got something from this
00:50:05 --> 00:50:07 conversation, share with someone in your world
00:50:07 --> 00:50:10 who will benefit from it. Share the show wherever
00:50:10 --> 00:50:13 you listen, subscribe, so you don't miss out
00:50:13 --> 00:50:15 on the next episode. This is Wassia Kamon, and
00:50:15 --> 00:50:17 it has been the diary of the CFO Podcast.