An AI “Perfect Storm” Is Hitting Regulated SaaS. Are You Ready?

Automated transcript

Gina Marrs 0:05

Welcome to TechRound Live. On this lovely Tuesday afternoon. TechRound brings you all the latest in tech and startup news from around the globe. We give a voice to startups and founders sharing startup profiles, founder features, funding news and a whole lot more. We also run monthly industry based competitions that shine a spotlight on both emerging and established businesses.

My name is Gina Marrs, I am Editor at TechRound. And today for our first ever LinkedIn Live, we're talking about SaaS. But not just SaaS. Experts predict that regulated SaaS businesses are currently facing an impending AI perfect storm. If they're not properly prepared, they risk being particularly vulnerable to a plethora of very serious challenges.

Joining me today is Alastair Cole, Co-founder at Scail. Alastair, welcome to TechRound Live.

Alastair Cole 0:45

Gina. Hi. Good afternoon, thanks for having me. It's great to be here.

Gina Marrs 0:45

Awesome. So Alasdair, let's just start off. If you can introduce yourself, tell me a little bit about yourself and your professional background before Scail.

Alastair Cole 1:07

Sure. Okay, thanks Gina. So I'm a computer scientist, an ex software engineer with two decades experience working with senior leaders in regulated industries, in law, in financial services, in telecoms, helping them navigate complex transformation, so particularly where technology and commercial performance intersect.

Gina Marrs 1:31

All right, awesome. And you launched Scail on 14th April alongside your co founders who will give a little shout out. We've got Douglas Cole, Alastair Mackey, Tom Cogodi, Al Conley and Jackie Fesset. Can you talk us through the founding team and why you brought together this particular mix of expertise?

Alastair Cole 1:50

Sure. Well we're a team of experts as you've run out there across engineering, governance, risk, technology, data, culture, brand and creative. So we've got a full suite of skills across the entire group.

And we deliberately built Scailas a multidisciplinary team because the biggest AI challenges are those that pervade the entire organization. And some of the challenges we're seeing with regulated SaaS, businesses and others is that they're developing AI capability in pockets and not across the entire organization.

Gina Marrs 2:31

Right. And I guess further to that, what problem are you seeing in the market, now that made you decide that now is the right time to launch Scail?

Alastair Cole 2:31

Well, it became clear to us over the last 12 months that AI wasn't just another wave of innovation, that it's fundamentally changing how values are created, how decisions are made, how businesses are operating, and Scali is a direct response to that.

And what makes Scail different is that we don't just build AI, we're stopping the common failure points that prevent AI from becoming safe, becoming adopted, truly being trusted, and being commercially impactful.

Gina Marrs 3:15

Okay. So maybe potentially pushing further beyond what a lot of, other, you know, what you're seeing other offerings from competitors in the industry.

Alastair Cole 3:15

Yes. I mean, everybody's been running pilots for 12 months now, or more.

And it's true that we're moving from experiments, experimentation into expectation now. Right. The opportunities are huge and quite a lot of businesses are, seeing the benefits of, rolling out AI across their businesses. But the pressure is intensifying for those that haven't rolled it out, they haven't got great adoption, they're not seeing value from their pilots.

And there's some significant challenges that are making 2026, truly a perfect storm for regulated SaaS businesses.

Gina Marrs 3:53

Yeah, absolutely. And I think in AI, it's. We've kind of moved beyond the point of, of AI being shiny and, and exciting.

It's still exciting, but it's now actually, you know, how, how do we implement things? How is everyone? How do we make things safe? How do we make them work? So I think maybe also on that note, how do you think this is? Did the Scail, the idea for Scailevolve from your previous work or how, did it come up kind of in this like, AI storm and just the rise of AI?

Alastair Cole 4:34

So I think, I think for the six of us, the six of us who've launched Scail as co founders, you know, we. The most interesting, the most, challenging work we've done over the last 12 months was unquestionably in the AI area. And so, finding this group and putting this group together and that was one of the things that we had in common.

And we realized that it's a fundamental shift not just in terms of the technology. We've seen that over the last few crazy months of 2026. And I'm keen to chat a little bit more about the developments that have come up.

But, this is going to be a much bigger organizational change. And I think we'd all seen in our individual areas the potential for capability building in AI, but that it was still very siloed. And that's why we wanted to build a multidisciplinary team to try and solve these problems.

And to go back to your question about why now for regulated SaaS. Well, there's three or four major forces happening, at the moment, that are impacting regulated SaaS businesses. The first is that the traditional software model is wildly under threat from AI.

The SaaSpocalypse announcement in February of Anthropic's, bevy of technical components means that software businesses are entirely rethinking where they are. The announcement of that technology wiped $300 billion of software tech stocks in software and cybersecurity.

And across the board, regulatory pressure is also rising very fast. You know, various industry regulators, expected to publish their AI guidance by the end of this year. But crucially, on 2 August the EU AI act comes fully into force.

So that regulatory pressure is rising. Right? And at the same time as shadow AI usage is off the charts, 78% of AI users are bringing their own tools to work. And when you put that shadow AI usage against the regulatory challenges that are on the cards this year, it's a very dangerous place for these businesses if they haven't got their AI use squirreled away.

And then finally the value that is being extracted from AI and it's partly due to the fact that too many people are focused just on pilots and not on the integration and adoption of those pilots into their broader tech stack and their working practices.

So more and more value is being demanded of AI champions, right? With less and less spend. You know, rising model compute data costs mean that there's a broader cost expansion going on. And even if you ignore the geopolitical instability that's driving costs everywhere, more and more businesses are being expected to deliver higher quality value from their AI work.

Gina Marrs 7:45

And that's where Scail comes in, right? So a lot of pressure, a lot to do and that's where Scail comes in to kind of help deal with those challenges and solve those problems. Right? So if you are talking to somebody who has never heard of Scail and doesn't know what Scail does, can you give us a brief synopsis?

Alastair Cole 7:45

Okay.

Well it's quite simple. We build AI capability for regulated SaaS businesses. We do it with clarity and control and decades of experience working with regulated businesses and across the consultancy world, we deliver measurable improvements, right?

Absolutely. Crystal clear that any kind of change needs to be measured. And those changes create real human value immediately and lasting commercial impact. And we've got deep expertise across three delivery areas of our business.

You know, we've got great jobs in diagnosing where businesses are, building AI capability, whether that's tech or culture and then operationalizing those across the organizations that we work with. And one of the things that we found most powerful is through our one hundred day transformation packages.

And these are bundles of products and services that we offer. They're bespoke, powerful packages that catalyze real change and move businesses from where they are to where they want to be in 100 days. We've got 400 day transformation packages that we use at the moment.

So we're not just theory, Gina, we're all AI practitioners, from everything from production strength, engineering capability, at big banks in the UK through workplace and adoption, cultural practices in order that people are skilled up using the tools in the right way.

But also that we're helping businesses communicate their AI rollout, all the way through to risk and governance expertise that we have in spades and ability to shape the narrative around how AI has been using businesses, how it should be adopted, how it's benefiting customers.

And so that full range of skills is why we built Scail . We saw in the market that that was missing and we wanted to come in and help those regulated SaaS businesses try and weather this perfect storm that's the clouds of which are massing on the horizon.

Gina Marrs 10:27

Right. So, the AI perfect storm is kind of like the most ominous thing that we've got, you know, on topic at the moment. Right. Sounds quite daunting and we've touched on it a bit, but let's get into that a little bit more. Can you tell us what exactly is driving that perfect storm?

You've touched on the EU AI act and. Yeah, let's tell you more about that.

Alastair Cole 10:45

Well, so I think, I think regulations is the first one and you know, it's not just the EU AI act, but also some of the government regulations and the regulators advice that's coming later this year.

You know, as data and technology grows, we're seeing regulation across all kinds of industries. You know, everything from marketing and advertising. And California just passed a law to ensure that businesses that don't include an AI watermark on their content are going to be fined heavily.

I think the EU AI act, which comes into force full force on 2nd of August, which is 96 days away. Gina. I think the potential fines for that are absolutely enormous. I think it's something like $35 million or maybe 7% of global turnover, which can be levied on businesses that are in full foul of that legislation.

So the regulations are a big deal. Shadow AI as I mentioned is a huge deal. You 78% people are bringing their own AI agents to work. But also they're, they're very hard to govern. A lot of the major platforms, you know, including Nan Breeze and Watson X, don't have any documented stop options for those agents.

So these agents are often running amok. At an AI Healthcare event last week, I heard a story that Google Engineer had let one of its agents run away and consumed like an entire quarter's worth of that team's tokens, overnight.

So that kind of ungovernable agency is a big part of shadow AI. The third area is that old software models are broken. AI is rewriting not just regulated SaaS but all software business models.

Throughout 2025, Spotify shipped 50 plus features that were all AI assisted development. And we're seeing the roles of junior and senior developers change enormously. The power of those engineering teams now is unprecedented.

The fourth area is human skills, kind of the structural skills gap that exists. You know, I think 78% of executives driving AI use, they're non technical. And at the same time there's a growing trust deficit.

We all question the output that we get from our large language models. And that's no surprise because hallucinations are everywhere. Unreliability is the number one concern users have about using AI. I think the 27% rate of unreliability is the biggest drawback.

So that structural skills gap is a big one. And then the last one is something I've touched already, which is that value, right, and costs rising quicker than ever. And the truth is that businesses that are only focused on pilots and not building them out properly and operationalizing them, are seeing that adoption is stalling before ROI is delivered.

I think 88% of companies regularly using AI are only seeing measurable gains or gains that are plateaued because they're not able to follow through. Because anybody can build AI tech today, that's easy. It's the communication of how that works, it's the adoption of that from a skills point of view and the integration of that into the workforce that is missing.

And so companies are being pushed, AI champions are being pushed to deliver more value from less spend. And when you put those five things together, with the SaaS apocalypse that happened in February, the EU AI act, and then let's just talk about mythos in the last month, the month of April has been dominated by anthropics, mythos.

And that's added to the crazy start to the year. You put all of those things together. Regulated SaaS businesses, some of them are facing a potential existential threat right now.

Gina Marrs 14:54

Yeah, absolutely.

And I think it's obviously important. On the one hand we have this existential threat that is stressful and it's looming. But then there's also, also risk involved there. Right. There's a lot of pressure to adopt AI quickly but I mean do you think that there are companies that are being pressured to adopt AI too quickly when they're not ready?

Alastair Cole 15:36

I've absolutely no doubt of that. Right. I think, you know, you look at the classic kind of adoption curves, right. You've got your, your, your early innovators taking it on early, you've got laggards at the back. I think, you know, a lot of businesses will be playing with this for a long time.

Those that haven't and those that feel they're a bit behind the drag curve. Yeah, naturally they're under pressure. They would have been under pressure if it was a normal technology shift. But this is a different beast, right? This is an entirely different beast. Partly because of the recursive nature of it.

Working with agents to improve your prompts with other agents to deliver software code is a kind of multiplier effect. And so those that are only starting now, yeah, they're under extreme pressure to accelerate.

And I think February's Saspocalypse was a massive moment. Businesses we're talking to are under extreme pressure to accelerate their adoption at the moment. And that's happening across all kinds of business.

You know, but particularly for regulated SaaS, they've got super high trust requirements, strict compliance obligations, they've got complex workflows, and AI is weakening their seat based pricing.

We're seeing a massive shift in pricing at the moment, towards tokens. GitHub did it, announced it just last week. And this move to tokens is making standard business features easier to copy. It's shifting buy expectations from access to software towards measurable outcomes, and making people focus on safe automation and provable trust in these systems.

And so, yeah, businesses are under pressure and I guess there's even more of a likelihood that they will launch pilots and embark on programs without checking a couple of key things. How, what is the readiness of their business to generate value from the Pilots and the rollout of the AI they're building.

But also, to understand their risk, their current risk exposure when it comes to AI, as well as value. And there's this light and dark that's going on. Everybody sees the light side, which is the real power, the potential of using AI.

At the same time you've got that dark side, right? You know, you've got compliance. Growing risks with shadow AI are getting out of control. And you know, if you're not on top of it, then you could be creating enormous technical debt and digging yourself a really big hole.

So, yeah, you're right. A lot of businesses are under pressure to accelerate their AI use. And really what they need to do is kind of take stock before they start, before they scale things. And that's where one of our products, the AI Risk Value Scorecard, comes in to ensure that they've got their ducks in a row before they take any further steps forward.

Gina Marrs 18:49

Right, Absolutely. So, I think you've summed it up quite well there in terms of the fact that it's a balance between not wanting to move too fast, but needing to move fast enough. Very difficult balance to strike. And I think, yeah, let's talk about the AI Risk and Value Scorecard because that is offered as kind of a solution, right, to this issue to evaluate AI readiness.

Alastair Cole 19:15

Yeah, I mean AI readiness is essential. Everybody knows they need to get moving. Everybody wants to see that value. The truth is that it's very easy to get into hot water. Right.

The AI Risk and Value Scorecard is a product of ours that we've built over the last 90 days. It's a structured way to continuously measure where AI increases risk, and where it creates, where it has the ability to create value.

It helps businesses understand what to stop, what needs to be fixed and also what to scale. And we analyze the AI capability of SaaS regulated SaaS business across eight core areas with about 120 metrics, and the result is a complete snapshot view of how AI is both performing across your business, but the risks that are there and the capability to extract greater value.

Gina Marrs 20:21

Okay, cool. And I mean, have you noticed so far, have you noticed any common patterns that have come up with, where companies are strongest or weakest in looking at the scorecard?

Alastair Cole 20:21

Yeah, so the businesses that we've assessed tend to be pretty strong in data and technology.

They've got strong engineering teams, they're able to build things quickly and so they tend to score pretty well there. Areas that they don't score well in are things like kind of commercial alignment and the value design. Right. I think only 50% of businesses are actually doing any kind of setting any measurement or metrics for their pilots.

So the commercial alignment, value, value design is one of the eight areas that we're seeing. Businesses do not score particularly well in strategy and prioritisation. They're pretty good at strategy. These are often ambitious businesses who know where they want to go and they're strategically quite strong.

But the prioritization of use cases of which pilots to launch, which to kill, which to improve is missing. And then governance and risk is another area where businesses could be doing better.

Gina Marrs 21:23

All right, and that's really great advice for companies who are maybe dealing with these issues.

But let's say for companies who have completed the scorecard, what happens after that? Where do they go from there?

Alastair Cole 21:47

Well, the scorecard contains or the report that we put together, the scorecard contains three key deliverables.

One is a deep dive into each of those eight core areas, and a scoring of those sub elements. We also produce personalized bespoke recommendations for each of the eight areas and critical next steps, for the business that should be taken in the next 30 days in order to get them back on track.

And then we also create a risk and value roadmap, so what the next hundred days looks like, through one of our 100 day transformation packages. And so we actually provide practical next steps across, across eight areas of business in order to, you know, accelerate value and mitigate.

Mitigate risk. So you know, we're not just theorists, we're all AI practitioners, the six of us and new people that join the business will be also. So as builders we are, you know, uniquely positioned to be able to make recommended strategic recommendations but also deliver the practical tips of how change needs to happen across, you know, adoption, cultural capability, tech and data, and communications, brand and creative as well.

Gina Marrs 23:21

Yeah, and that's really important. I think, identifying issues and pointing them out is one thing, but actually giving practical solutions and a roadmap with how to deal with it is something entirely different and incredibly valuable going forward.

Would you say?

Alastair Cole 23:37

Go on.

Gina Marrs 23:37

No, continue.

Alastair Cole 23:37

I was going to say we're very hands on as well. And so the 100 day transformation package that we put together, those are delivered through short sprints you know, two week sprints effectively across a 14 week period.

And our sessions, whether they are on risk or governance or capability or adoption or tech and data, they're all very hands-on. And so we run a lot of live sessions with our clients where they get to see us experimenting, playing with and they get to see behind the scenes of the AI tools and platforms that we've built.

So we're a very, very hands-on organization. We like to show clients what we're thinking and how they can make those changes. It's not just a kind of report based consultancy. So in the same way that AI is light and dark, we're both theorists and strategists but also hands on builders and practitioners for sure.

Gina Marrs 24:46

And so what would you say for Scail , what does your success look like going forward in the next 12 months? Where would you like to see the company?

Alastair Cole 24:46

Well you know success for us is helping regulated SaaS businesses, right to get some, get greater control, build their confidence not just in tech and data where it's strong, but across the board, rolling out the organization.

We want to help them take the ambition that they have, which is definitely currently unfulfilled and move that into you know, actual advantage, actual measurable improvement in their business, and we aim, we're able to do that within 100 days to demonstrate measurable improvement and real human change or real human value, sorry, that delivers lasting commercial impact.

So that's what we want to do. We want to help those businesses move from fragmented experiments to coordinated capability and from unproven initiatives to measurable and crucially defensible commercial outcomes.

Because the ability for small startups or individuals, at home in their bedrooms to create incredibly powerful software that is a reality now. And so these businesses both need to rethink their product roadmap, they need to build their moats around their product and they need to come to grips with the rapidly changing regulatory and technology landscapes that are out there.

And they've got to do all that while they're doing their day job as well Gina, running their business, sorting out the commercial aspects on tokens and how billing is going to happen but also how their workforces work, how their engineering teams work and they've got so much to deal with there, having a trusted AI navigator like Scail to oversee how AI is rolling out across their entire business.

We think that's something that they need from an entity like Scail . And so what success looks like is helping those businesses, to stop waking up, that either of those businesses stop waking up in the middle of the night, sweating about what could be and in a positive way, but also mitigate the risks of, of what could go wrong. Right.

Gina Marrs 27:25

So let Scail jump in and, and take over some of that stress and deal with some solutions. Right. And Okay, so, yep,

Alastair Cole 27:25

I was going to say, yes, having a safe pair of hands to help your business navigate its way through this, you know, insanely, changing landscape.

You know, if you look at February, March, April, just of this year, it's, it's been, it's been wild. The number of changes. And so having an expert on hand with our finger on the pulse of all these different aspects of, of AI, you know, from governance and risk to data technology integration, communications and adoption, all the way across the, across the life cycle, the AI lifecycle businesses.

We hope that that's something we'll be able to bear for them.

Gina Marrs 28:14

And for. If we have SaaS companies listening, founders, what is the next step for them?

Alastair Cole 28:14

Well, the next step for them would be to reach out to Scail, obviously. Right.

But you know, I mean in terms of SaaS and the, you know, the SaaS apocalypse that happened in February and also the, the Sasplosion, as my brother would say, that is coming right, as every man, woman and their dog is going to be able to create new platforms.

Whether they'll be production strength, whether they'll be adopted or not, that's a separate matter. But while we're very early on in the kind of capability of this new SaaS power, the consequence is already massive. You know, the expectations, the scrutiny, the competitive pressure that's coming on to regulated SaaS businesses is high.

So you know, we hope that they're able to move fast and you know, transform internally in the face of these challenges. And if they've got any doubts about that, then they should reach out to us at Scail with AI.

Gina Marrs 29:38

All right. And I guess the next step would be to try out the risk, the AI Risk and Value Scorecard. And next steps from there would be to work with Scail.

Alastair Cole 29:38

Yeah, absolutely. Trying the Risk and Value Scorecard. Yeah, there is scailwithai.com forward/scorecard Is where businesses can go and get more information about that and reach out to us and find out how we can help measure their risk profile right now.

And also the value that they ought to be extracting from rolling out this powerful new technology.

Gina Marrs 30:13

Right. And creating a roadmap for the AI future.

Alastair Cole 30:13

Right, yeah, absolutely. That roadmap is absolutely key.

Gina Marrs 30:29

Right. So we have a few questions. If you are ready. I'm just going to go ahead and shoot. So firstly, what are the burning platforms or worry beads that you see that you are seeing for tech firms?

Alastair Cole 30:29

Okay.

Well, the, the, the, the kind of, the, the four Horsemen of the apocalypse, I've touched on them a lot. You know, the first one is, is risk. Right. You know, not only have we got these deadlines looming, people are asking, do they have control over their AI use?

The businesses we talk to, a lot of them don't even know how far the shadow AI use extends. And are they exposed from a regulatory standpoint. Right. You know, compliance, regulation. These are essential areas for software businesses.

So one of the big concerns is risk. Another is value. Are they creating value or is it just activity that's going on inside the business? You know, at the AI event last week, we had experts from Capgemini, AstraZeneca and others.

And you know, when I asked the question in the panel, even those businesses, they're not assessing their capability to extract value from their AI programs before they start. They're just starting. Right. And so being able to work out what value should be extracted from this is massive.

There's no point just having AI activity. Right. That's not going to win. That's not going to win any, not going to keep businesses alive anymore. It's got to be about delivering measurable improvements. The other worries, I think there's a big human worry.

I feel like we're getting over, people being worried that AI is just simply going to take their jobs because more and more components of working life are being powered by AI. It's humans augmented by AI now.

And that's going to pervade. I think that's a question we've got over. It's now really about trust, right? Trust in the output, trust that these systems are actually telling the truth. So that's a big concern. And also, trust in the process to a certain degree, because, you know, adoption is really important.

Training, learning, culture, these are, these are essentials. And some businesses we talk to, their staff are, you know, they're seeing AI fatigue in terms of, you know, it's another training course. Right. And so how that's couched how those sessions are delivered, whether they're just one way, you know, tutorials or whether they're interactive hands-on sessions like I talked about earlier.

That's huge. And then, and then you know, the product, you know the, the obsolescence or potential obsolescence of SaaS products is going to be huge. Is it defensible for existing products, do they need to, how do they need to be transformed in order that they're going to be around in 12 months?

How do development teams change? How does the way that they go about building new features and rewiring their platforms? These are all product concerns that are live right now. And these are all board issues, Gina. Right.

These are not just technical issues, these are human issues. These are board level issues. That's what we're hearing is keeping businesses awake at night.

Gina Marrs 34:00

Right? Fair enough. Those are some pretty, pretty poignant questions and things to consider.

Okay, next question. You've spoken about the SAS apocalypse, which is a great term by the way. Do you think is the SAS apocalypse a real thing or is the threat overblown, overhyped,

Alastair Cole 34:17

$300 billion wiped off, you know, tech and cyber security stacks, I would say is, is, is a real deal. Right?

It's a big deal. And the truth is that with the, these new programming tools and they are phenomenal, you know, in the hands of our engineers we were able on Friday last week in three hours to build production strength, AI powered, customer tools that sit on AWS stack, have full secure login that the power that we've got now and so the power that these business have is enormous and the power that everybody in their garage has.

So like features are easier to copper now copy which means pricing is under extreme pressure. You know, and you know we've seen a precipitous decline in the number of people choosing to read computer science. Right, which, which, which is followed on from these new development tools.

And you know what that, what that suggests is that you know, the democratization of the ability to create technical products, to create SaaS platforms I.e. just, that's pervasive now. And so it's completely changed the game.

You know, junior developers are, they're having to learn the ropes of software engineering in their roles in double quick time, while at the same time learning how to use the very latest AI models and techniques. Because they can't just start on AI, they have to have those software engineering fundamentals, otherwise they won't be able to check the work that comes out of AI.

They won't be able to stitch together the AI platforms and tools that are built properly. And then for senior developers, right, in the SaaS world, they're being driven to maximize their token usage, right? They're developing new skills in terms of orchestration of agent teams and the interoperability of systems and data.

So that SaaS world, right, that's as a result of the SAS apocalypse that is just, you know, it's exploded and it's changing, it's transforming at, insane pace. You know, it's not the end for software by any stretch of imagination.

It's just another reset. Right? And my gut feeling is that, actually computer science as a discipline will just evolve fast, right? As it's done repeatedly in the past, as it did with the arrival of cloud computing, from a Scail point of view, as it did with machine learning, from a deep learning point of view, as it's done with cyber security and trust.

So software, software engineering, computer science will, will, will morph again as it's done so many times in the past. And the winners in the SAS world were those that focus their AI efforts on measurable outcomes, on the workflows that unite their teams, on building things that create trust both internally and externally with customers and those that develop domain expertise, depth in this new emerging software field.

Gina Marrs 37:43

Right? So not quite the very end of the world and end of SaaS, but big changes, big changes.

Alastair Cole 37:43

Lots of work to do, lots of thinking to be done, lots of experimentation to be had, experimentation to be had, all weighed up against the potential risk of some of this technology.

And Mythos has shown us that the risks are enormous. And when you put all this together, that's what some people think. That perfect storm is a little bit strong, but actually when you put all that together, there's an existential threat for a lot of SaaS businesses.

Gina Marrs 38:03

Yeah.

Okay, I want to shift a little bit to, we've got a couple of questions that maybe look kind of at the, some of the social, the social side of this. And firstly, what is the culture gap currently in organization when it comes to AI adoption?

Alastair Cole 38:20

Right, well, that, that's, that's a great question, you know, and as the tools are becoming easier to use and everybody can use them, and that's democratized the product, the problem shifts not to whether you can build something quickly, but, but can you build something good?

But crucially, how is that adopted? How do people perceive that? How is it communicated right from the start? And we're seeing a repetition of the kind of it led projects in the past where often it would just crack on with new systems and not bring other teams and other departments in until right at the last minute by which time it's kind of designed and it's a fait accompli.

And obviously that doesn't go down very well. Right. Anybody, nobody wants to be invited to the party at the last minute. And so it's even more important given the pace of change now that the right teams, the right people across an organization are brought in at the start not necessarily to make decisions but to contribute, to be aware of what's happening.

So the communication of these new initiatives is critical and without that you're not going to get the kind of cultural adoption right that is needed in order for these not just heavy pilots but to be proper builds that can be operationalized and that return on investment will be seen because it takes many months for these to take hold across the entire organization.

You can measure adoption early on with your core group but these things do take time to roll out. And so there is a culture gap in terms of adoption. You know we're still relatively early on when it comes to the kind of adoption of these large scale systems.

We don't have a huge amount of experience. Nobody does because it is relatively new. But what we're seeing is you know, inconsistent usage, low trust, shadow AI use anyway, anyway. And the truth is that capability is not built through tools, it is built through people.

Gina Marrs 40:53

Absolutely. And people are such an important part of adoption and making these things work in the long term and you can't do it without them. I think opening the conversation and making sure that everybody is part of the conversation and participating is absolutely crucial and it's not something that can be forgotten.

Final question sort of pushing on a little bit from that is how do we ensure that everyone benefits from AI and that it doesn't widen already existing inequality gaps?

Alastair Cole 41:13

Sure. Well I mean you touched on it there. You're talking about getting the right people around the table at the start.

And you know, Tim Burns Lee, founder of the World Wide web, said 99% of the world's problems are communication problems. And he's right. That early communication about what's happening, what we're going to do, digging into the value that can be Created or the risk of the moment.

Early work is absolutely critical. And then, you know, after that, the priorities, I would say, is ensuring that capability is universal. Right? It's not elite. Everybody gets to, exposure to the tools and the training. Right?

They should be role based. Should be organization wide. Or the access should be, we should see defined, really defined standards, not just tools. Because clarity builds trust. Right?

When you know what's going on, then confidence increases, trust increases. And then we're designing. Everything should be designed for enhancement, for augmentation of humans. It's not about replacement. And so that's a really important message to communicate.

This is about making people better, not making them redundant. And the organizations that get those, those things, right, they're going to be building stronger, more inclusive teams where people are sharing their knowledge, sharing their tips, sharing their tools.

And that is the future of work. Because, you know, it might feel like this is, we're kind of all jumping off a cliff. But the truth is this is an evolution, right? This is an evolution of workplace practices. AI is only going to increase in terms of its quality and it needs to be adopted, integrated and championed across organizations, across the entire organization to ensure that they're successful.

And that's why the six of us got together. That's why Scail exists, because we believe that building capability in AI requires a full service approach. And that's why we've built Scail as a full service growth partner for regulated SaaS businesses.

Gina Marrs 43:39

I think that's a great full circle moment because we think about this a lot, but companies are all about their founding teams and the people that are part of the businesses. And at the end of the day, when it comes to AI and when it comes to SaaS and regulated SaaS, you're building four people.

And so it's obviously really important who the people that are building for the people.

Alastair Cole 43:58

It's all about the people, Gina. It's all about the people.

Gina Marrs 43:58

It's all about the people. Always comes back to that. So I have one more question for you. We spoke a lot about SAS, regulated SaaS, AI SaaS apocalypse, all of the ominous things.

You've also raised the Mythos situation. And I wanted to just see, is there anything, anything particularly interesting in the world of AI that you think we should be thinking about, and talking about beyond what we've already spoken about?

Alastair Cole 44:20

Well, I mean, Mythos is a, is a, is a, is a fascinating story.

I mean, basically Exactly. Pretty much 30 days ago, anthropic accidentally, announced, or it was Mythos story broke because somebody had left some notes in a.

In an unpublished blog post. And you know, Mythos is this technology that has the power to find vulnerabilities in. In software, in finance systems. And so, you know, it's. It's big. It's a huge deal. It's very powerful.

It's been given to a closed group. But, you know, like you just said about. About the people. Even the Mythos story, if people go and research that, you can see what's happened. But, you know, it's all about humans, right? Ultimately, because humans found it, human error resulted in the story being found.

The vulnerabilities that Mythos tracks down and helps you find out, human errors in system design, and then human failures accounted for, Mythos getting hacked, 10 days ago or unauthorized access being granted.

And you know, the truth is when you think about when you remove the tech and everything else, the truth is that human fallibility, our ability to miss stuff, just rises, to the level of technology. And whatever tech comes out, we're always going to make mistakes.

And so, it's essential that you've got all your risk mitigation plans in place, as well as the value. But, yeah, the Mythos story is something that's grabbed my attention over the last 30 days. And, and. And, you know, that's.

That's like April, right? It's a sad apocalypse kind of all happened in February and exposure. So we had a little January off and February went wild. You know, there's more stuff in March. Then April's exploded with Mythos, like, what's. What's coming next? Gina, I mean, you should know you're sat on the, you know, the editor report at Tech Round.

You should have a crystal ball, I would imagine, of like, you should be telling us what's coming around the corner,

Gina Marrs 46:38

Alastair. Well, I think sometimes the more, you know, the more, concerning it is. So I guess we'll just have to see. May is coming up fairly soon, so I think we'll be. We'll be hit with that in the coming days.

Hopefully no more, apocalyptic issues, but we'll. We'll find out soon enough.

Alastair Cole 46:55

Yes.

Gina Marrs 46:55

All right, so those are the questions that we have for you today. Thank you so much for chatting to us. Is there anything more that you'd like to leave us with? In terms of Scail and what you have to offer?

Alastair Cole 47:13

Regulated SaaS businesses. I think maybe just if people are interested in finding more about Scail, they can head over to our website, which is at. Yeah, thank you. At, scailwithai.com, you can read more about us and, find out about our Risk and Value Scorecard at scailwithai.com/scorecard where you can get more information about that.

Gina Marrs 47:45

Awesome. Sounds good. Alastair, thank you so much for joining me today. We spoke about the AI perfect storm, the challenges facing regulated SaaS businesses. And you've told us all about Scail, how you and your team are ready to guide companies through the storm, the metaphorical storm.

You've spoken to us about your AI Risk and Value scorecard and how companies can use the scorecard to develop their own AI roadmap. I'm very much looking forward to seeing Skale grow and develop over the coming months and years. And on behalf of TechRound, I'd like to wish you and the Scail team all the very best and on this really exciting journey ahead.

Alastair Cole 48:22

Thank you, Gina. That means a lot. I appreciate it. Thanks.

Gina Marrs 48:22

Fabulous. And, to everybody watching, thank you for tuning in. Thank you for joining us for our first ever TechRound live on LinkedIn. TechRound also has some really exciting things coming up for 2026.

We are wrapping up our FinTech50 competition today. Entry scores at 5 GMT. So make sure to get those entries ASAP. You can find the entry form on the website. Coming up in May, we've got the AI 45 competition.

In June, we've got the Mena 40 July, our Health Tech 44, and a whole lot more competitions, as you can see coming up for the rest of 2026. So have a look at the website and you can find the full calendar for the year. For any inquiries about publishing with TechRound you can also contact us, you can see my email address there. Visit the website.

We love to do founder features, Startup profiles Found of the Week, Startup of the Week. If you think that you're a good fit, let us know. If you would like to launch with TechRound, we would absolutely love to hear from you. Whether you're a startup, whether you're launching a new product, an event, anything exciting, we would love to hear all about it, let us know.

That's a wrap on our first ever LinkedIn live, talking about the AI perfect storm facing regulated SaaS companies. Today we spoke to Alastair Cole, of Scail, and I'm Gina Marrs, editor at TechRound, bringing you the latest in tech and startup news from around the globe. Great.

Alastair Cole 49:57

Well, thanks, Gina.

Gina Marrs 49:57

Awesome. Thank you so much, Alastair. Bye.

Alastair Cole 49:57

Bye.