Turning vision into value: Why private equity-backed firms must rapidly adapt to the AI revolution

They’ll be able to test those products quickly, then easily adapt them based on insights gained and iterate at pace.

Companies will be able to rapidly adjust their products, create multiple variants, make huge pivots – or anything in between – in response to changes in market conditions and new opportunities, all the while creating outputs of higher quality.

And all this will be possible at significantly reduced cost – thus negating the need for large amounts of high-risk, early-stage funding. Instead, investors will be able to place their bets on an MVP, or adaptation of an existing product, that is already proven to be successful and scalable.

In all of the above, the potential value will be created by the smart integration of the right AI tools to accelerate and refine processes at every step.

However, this isn’t the distant future. In many cases, it’s already happening.

Yet for many firms – particularly those backed by private equity (PE) investors – the reality isn’t always matching up to the vision.

So why does this gap exist?

Overcoming the blockers to AI-driven value

Because a typical PE investor will be looking for a substantial return over a period of three to five years, many initial investments will have been made prior to the explosion of generative AI tools that are now massively disrupting almost every industry. Usage of these tools may not have been part of the original investment thesis – but they absolutely need to be now.

However, too many organisations are failing to keep ahead of the game and unlock the enormous potential value that AI tools can deliver.

In our experience, the main blockers are as follows:

1. Time constraints

We are seeing many companies suffering from a simple lack of bandwidth to explore how best to leverage the capabilities of AI.

This is often compounded by intense pressure to deliver results against the original investment thesis. Pressure builds on top of pressure as new opportunities for growth are discovered or acquisitions are made which then need to be carefully integrated. This can leave little room for reflection or experimentation with new tools.

Add to this the rapid pace at which AI tools are constantly evolving and improving, and it can seem almost impossible to keep up – let alone move ahead of the game – when it comes to understanding the best ways to deliver practical, value-driving applications of the technology and successfully roll them out across the organisation.

2. Hype versus reality

As has always been the case whenever a new, heavily hyped technology floods the market, most AI tools are currently not mature enough to deliver fully on the promises made by their vendors. There is no doubt whatsoever that AI is a game-changer. But being able to work out the difference between the sales pitch and the practical reality can be challenging and requires deep expertise.

3. Security, legal and compliance challenges

Legitimate concerns exist around issues such as security, regulatory compliance and IP-protection – many of which are yet to be clarified and resolved. While most AI tools offer, for example, zero data retention and assurances around IP, understanding and mitigating these requires time, experience and focus – for example, in ensuring the tools are correctly configured to be fully compliant.

Overall, it’s vital to address these issues. And soon.

If your company takes too long to release new products or new features, you may quickly find yourself in trouble as your time to value becomes severely eroded. Your new competitors – who could be almost anyone armed with the right AI tools and the ability to use them effectively – can already enter the market and pull the rug from under your feet, able to adapt to market demands and seize opportunities far faster than companies with legacy platforms and products.

Learning from best practice

So how can you start turning AI into tangible value?

We believe that working with a skilled and knowledgeable partner is a powerful first step. Ideally, you would choose one that is constantly tracking the latest advances in AI technology and how they can be applied– safely and legally – to deliver greater value in the shortest possible timeframes.

They would also be able to consult on best practice, drawing on their own experiences in the field alongside those of similar clients they have supported.

The aim would be for them to help you deliver high-quality outcomes using the most effective AI-enabled processes and techniques.

To address legal and security issues, it’s essential to have an AI policy in place that creates the appropriate guardrails for safe and compliant usage of AI. Above all, we strongly recommend that absolutely everything always remains subject to human accountability – so have your people reviewing and refining every AI output at every stage of your processes. Here at Damilah, we do – and always will.

Last, but not least, there needs to be a shift towards outcome-focused roles. In other words, enabling AI tools to handle more of the laborious, time-consuming, detailed technical work – thus allowing a skilled human workforce to maintain oversight while concentrating on value creation and strategy.

New pricing models and investment strategies

And here’s one further thought. It’s likely that agentic AI tools will soon become prevalent in many organisations, which may have a profound effect on commercial pricing models.

Instead of the traditional pay-as-you-go or seat-based SaaS pricing structures, we may soon find outcome-based pricing models becoming the norm – that is, where fees are based on successful delivery and results.

This, in turn, would require PE houses to review – and radically adapt – their investment strategies, resulting in major impacts on the organisations they back.

It’s too early to predict precisely how this AI-powered future will unfold. But one thing is certain: all organisations – and particularly those funded by PE – need to remain fully alert to the fundamental shifts that are occurring and be nimble enough to rapidly adjust. Those that don’t risk becoming dead in the water.

We can help you transform your AI vision into genuine value . To explore the possibilities, get in touch now.

Iain Bishop, founder and CEO, Damilah