F&A Leaders Deploy Agentic AI to Close Faster and Cut Costs

Heat. Heat. Heat. Heat. Heat. Heat. Heat. HEAT. HEAT up here. Thanks for joining us today. I'm excited about this um because I know this and soon you will see this but we have an amazing panel of innovators, practitioners and experts on the webinar today. Uh first I'll introduce myself. Uh my name is Ian Barkin. I am co-founder and co-CEO of Magentic. Uh, and I have the distinct privilege of being your moderator for today. Um, we've got a great and greatly useful session lined up. And to kick us off, I'd like to go around the horn and have every one of the panelists first introduce themselves. So, I'd like to start with Kelly Dunn, please. Kelly.

Hi, Kelly Dunn. I lead Georgia Pacific's finance transformation capability and am uh definitely in the weeds as a practitioner in this space.

Uh Tariq, you're next.

Hi everyone, I'm Tariq Munir. I am a digital transformation and AI advisor, a keynote speaker, trainer and I'm also the author of re-imagine finance which has just been released actually and uh yeah I have been working over in in finance and accounting space for last 20 years. So yeah excited to be part of it.

Perfect. Welcome Ver. And David Brain last but not least.

Thank you Ian. Uh so David Brain, I'm a fellow co-founder and co-CEO of Magentic. Uh I spent the last 20 years trying to um find new ways of uh improving companies operations, removing waste. First with outsourcing, then with automation and now with AI.

Outstanding. Well, thank you all. Welcome. Uh and we will get on with the show. Um so I'm going to give you a little bit of background on us first. Uh so my co-founder David David Brain and I have spent as he'd said um 20 years or more working with finance and accounting teams uh and we've done so across multiple different industries in financial services and banks in health care and insurance effectively complex industries often highly regulated industries and we've helped them to successfully both understand and do the research and then ultimately adopt and deploy advanced automation and AI technologies which has been a real privilege and quite a journey. Now, we a few years ago, we had a successful exit with our last AI solutions firm. And after some time, we realized um a I I realized I'm not good at golf, so I should do something else with myself. Uh but also, we realized we love this stuff. Uh and we love it too much to sit on the sidelines during this next wave of AI. Uh so, we've poured everything we've learned in the last two decades into Magent. Uh and ultimately at Magentic, we're typically engaged by one of two types of leadership teams. So one type of leadership team is leaders who know they need an AI strategy. Like everyone is telling them that every social media post, everything is saying you need an AI strategy. Uh but they don't know where to start. So that's one group. And and as the the stat showed, they're not alone. um or we're working with those leaders who are in early stages of experimenting as so many are on this call um as a means to help them grow their business, right? They're experimenting to see if they can scale without the linear demand of more headcount to do more work um or they're looking simply to just modernize operations and have more of an agentic or AI powered operation. The thing is that second group is often and you may find yourself in this position too. They are overwhelmed by the tech landscape, the hype, the noise, the marketing confusion, and often they're not seeing value from their current projects. And so, um, what you could do is you could have someone come in and just jam AI into various sort of nooks and crannies around your operation. Uh and honestly that's what we did a lot of at our last firm is we would come in and help implement AI. Um but what we saw was that often that doesn't lay down, you know, effectively a sort of a solid root base that you need for long-term impactful and valuable AI adoption. And so our approach at Magentic is different. rather than airdropping bots in and then leaving. Um what we do is we take on scopes of work for our clients. Uh so as an example, we do accounts payable processing. We do tax preparation. We do month support as examples. Uh and what we do with that is we do it by tapping into an amazing cost competitive global talent uh workforce. Um, and then we blend in cutting edge AI everywhere that it can be successful and safe. And that's key. And so ultimately what what the outcome is is we're able to achieve three things. Uh, one of them is dramatically lowering the cost profile. You know, by doing the work, by tapping into global talent, we're able to deliver 40 plus% savings at the very beginning of a journey. Uh, the second is then we increase the success rate of AI adoption just because we live and breathe the work. we actually do the work. And so we're able to find the areas that will drive real value through a safe and successful application of AI. And then finally, um, we deliver end to end. So this isn't discreet bits and pieces of a process. Uh, we take on full accountability for the delivery and the benefits. So effectively, you can sort of think of it as like an outcome as a service. And the good news is we've been seeing great success with this approach. Uh, and honestly, we've helped those sponsors of our work look like rock stars. So, those folks on the call who who said that they're doing that investigation, they're looking at areas, those are the folks we love working with because we make them look really good because we're both bringing home cost savings and an AI success case all at the same time. So, that that is the end of our commercial break. Um, obviously, we would be happy to share more after the event if that sounds relevant or interesting to anyone. Uh and I guess simply put, we would love to help you become the AI rock stars at your firm. Okay, so let's let's move on. Uh today on this call, like I said, we've covered introductions. Um I'm going to do a bit of scene setting and then we're going to have an outstanding discussion with a really good panel. Um but before um we get started, I'm going to do a little bit of that scene setting. So ultimately right now um as as you verified and as we've seen most companies are trying to invest in AI this year. It's no secret they're told they have to right. You need an AI strategy. You have to be using AI. Whether that's um boards, CEOs, CFOs, investors, whomever it is, they're being told they need an AI strategy. But this is all done in a context where hype hype is at an all-time high. Right? There is so much noise out there. This is obviously the Gartner um hype curve. If you've seen it before, everything at the top of that curve is in its noisiest, most exciting, but most often or more often than not, it then slides down into a trough of disillusionment. And Agentic AI is right at the peak of that. It could not be noisier out there right now for Agentic. And what's so exciting for us and again from this 20 years of experience, most operations have gone from manual workflows where you were basically um using humans to be the glue between the systems that ran your business to then robotic process automation which is where David and I have been working for the last 20 years where we got started um quite a while ago where you then started to use software to be that glue to create workflows that were more automated between your systems. And now we've entered an era where um the promise is AI workflows and even noisier and hyperier agentic workflows and AI workflows means you're tapping into a bunch of quite powerful capabilities now including all of the generative AI that you see from chat GBT and Bard and others or Claude and others. Uh, and then agentic workflows. That's a lot more um sometimes science fiction, sometimes marketing hype, and there's some truth to it, but there's more autonomy self-directed self-learning self-healing processes um that are pretty complex, and it's still really early now. All of that in the context of every headline now, and there was a recent one if you saw the MIT report about how 95% of AI projects fail. Um you know I'm not great at math but 95 is a really big number. So that is most of the projects are failing. Um what we tend to find is projects don't fail because of the tools being used. It's because of everything else. It's again that sort of the substrate the soil in which you planted those seeds. So more often than not companies just operationally aren't ready for this stuff. Um everything from they don't have a vision strategy a plan in place. they don't have processes documented, they don't have clean data. You know, data comes up all the time. Um, or they just haven't gotten the the organizational buy in and clear awareness of why are we doing this? Um, so that's one of the reasons they fail. The the hype certainly doesn't help when you're told by every vendor that you're talking to that this stuff solves all of your problems and lo and behold, it's easy. Um, that doesn't set you up or doesn't set them up for success. many times and ultimately results is somewhat underwhelming return on investment uh as far as was it worth it? Was this anything more than a science project? Um is this something we would do more with? And so um that is coloring some of the headlines these days and you are probably seeing these as well. Um that there's sort of a push back of you know Wall Street doesn't think that AI is adding value yet or projects are failing. that's that's not unnatural or that's not um not out of the ordinary in really interesting innovative sort of bleeding edge programs. Um but often the reason they fail is is pretty standard and um you know routine. Okay, so that's the setting. It is now um a with great pleasure that we get to to pivot and now bring in our panelists to start hitting them with the hardest questions I could think of. Um and let's go to the uh if we can go to