Last year Artificial Intelligence (AI) soared to the peak of Gartner’s Hype Cycle, meaning it reached its “Peak of Inflated Expectations”. But many organisations that have experimented with AI are already finding themselves stuck in the “Trough of Disillusionment”, the next phase of Gartner’s Hype Cycle, where initial excitement and promise give way to a more realistic understanding of the technology’s limitations and challenges.

If your encounters implementing AI have left you with a big bill and questioning what all the ‘hype’ is about, you’re not alone in your disillusionment. Despite the promise that AI will revolutionise organisations and industries, countless companies have invested a lot of time, effort and money into adopting AI, only to see their efforts falter. Shockingly, around 90% of pilot AI projects won’t move into production in the near future, and many will never progress.1

Navigating the pitfalls of AI implementation

There are a myriad of reasons why AI and data projects get stuck or fail. Many businesses, caught up in the fervour surrounding AI’s capabilities, rushed to implement it. They saw something shiny and new and worried that their business would be left behind if they didn’t apply it. Excited at the thought that AI could transform their operation, they started experimenting on use cases. The problem was, they did so without any clarity around the business objectives and outcomes. A clear case of introducing tech for tech’s sake.

In many cases companies were piloting the wrong technology to address the business need. In some cases alternative technologies would have been more suited to the challenge than AI. In other cases, AI was simply not yet mature enough to execute tasks in the production environment.

While there’s no doubt that when done right, AI can be a real revenue driver, it can also be a huge money pit. Buying an off-the-shelf AI solution might still be a viable option for some use cases, but hidden costs such as licensing fees, customisation charges and integration expenses can accumulate over time. Moreover, these solutions are designed to cater for a broad range of businesses and lack the nuanced understanding of individual organisational context, meaning they will never be a perfect fit for your business’s specific needs.

So how do you become an AI success story? Afterall, IDC is predicting that generative AI will add nearly $10 trillion to global GDP over the next 10 years.2 A lot of consultancies will tell you that success depends on having a ‘robust’ AI strategy. To some extent this is true, but a robust strategy will only get you so far.

Where traditional AI strategies fall down

We 100 percent agree that every project needs to start with a strategy. We also see huge limitations with the way consultancies have traditionally created, presented and implemented data and AI strategies.

Traditional strategies provide a static view - from the current state to a future vision. This is then overlaid with a tidy roadmap of how that vision will be achieved. The problem is, technology is evolving faster than most can implement it. And as for the roadmap – well, that road is never going to be straight. Let’s face it, quite often, by the time the strategy is finalised your business has already changed and evolved, rendering it outdated before you’ve even started.

The other challenge with traditional strategies is that they’re not easily accessible. Traditional consultancies will present incredibly impressive PowerPoints, but leave you completely reliant on them to interpret and execute the strategy. Without access to the wider picture it makes it almost impossible for siloed business units to understand what impact a decision or project will have on your organisation’s broader goals. And what happens to the PowerPoint? How often is it dusted off and revisited. More importantly, how often is it updated?

What’s the solution?

Ok, this is where admit we have something shiny and new to share. We’ve been doing what we do best and thinking outside the box. What if, having identified the projects that will have the biggest impact for your business and designed a feasible roadmap for production, your strategy is built using AI?

“What if your strategy understands how your business operates, understand your organisation’s unique context and continuously accounts for and incorporates changing circumstances? What if it’s accessible across your business, so different units and departments can constantly interact and engage with it to help support decision making?”

We call it a Living Strategy.

With our Living Strategy AI transforms from a tool into your most powerful teammate. And unlike traditional consultancy models which foster dependence on external expertise, our approach aims to empower organisations to take ownership of their AI evolution. That’s because we’re creating something that’s built to last. Your Living Strategy will be a durable asset that guides your journey as your organisation evolves – because it evolves with you. And the best part… you won’t be reliant on us. You’ll only need us once.

Own your AI evolution

As the landscape of business and technology evolves, so too must our AI strategies. With FOIL’s Living Strategy, we deliver more than just a roadmap; we deliver a dynamic, ever-evolving blueprint for success in the age of AI. And by rewriting the playbook and shifting the focus from consultancy dependence to organisation independence – you get to own your AI evolution.

Where are you at on your AI journey? Can you define your organisation’s objectives and vision? Have you identified clear use cases for AI? Do you understand how you will build those solutions? Do you have the right technology and skills, and have you considered legislation, ethics and security?

Are you ready to transform your AI journey from disillusionment to success? We’d love to hear your experiences. Do you think it’s time AI strategies evolved? Leave a comment below with your comments and questions, and sign up for more exclusive insights on navigating the challenges of AI implementation.

1 Forbes - Reasons Why Generative AI Pilots Fail To Move Into Production

2 Microsoft – New Study Validates the Business Value and opportunity of AI