How businesses are putting AI into action

That gap is where the real story sits.

At Elite Business Live, a panel of founders, strategists and technology leaders tackled a question many SMEs are quietly asking themselves. If everyone is adopting AI, why are so few actually benefiting from it?

The answer was not what many expected. It is not about the tools. It is about how businesses think, lead and operate.

Bringing a breadth of perspectives to the conversation, the panel featured futurist and author Andrew Grill, Dave Birss, co-founder of GenAI Academy, Kunal Kaul, Managing Director for Small and Medium Businesses at Cisco EMEA, Joe Seddon, founder and CEO of Zero Gravity, and Julie Holmes, AI strategist and founder of Rivet Labs. 

Together, they combined frontline experience across technology, leadership, and scaling businesses, offering a grounded view of what it really takes to move AI from experimentation to meaningful impact.

AI adoption is failing because businesses are solving the wrong problem

One of the biggest misconceptions discussed on stage was the idea that AI is primarily about productivity.

That narrative is everywhere. Faster. Cheaper. More efficient. And according to Dave Birss, it is holding businesses back. “AI is good at amplifying human ability.” This shift in perspective matters.

When businesses focus purely on efficiency, they limit AI to cost-cutting. When they focus on amplification, they unlock growth.

That distinction explains why so many organisations stall. They are trying to optimise what already exists, rather than rethink what is possible.

The hidden advantage most SMEs are missing

For many businesses, the starting point is closer than they think. Andrew Grill highlighted a simple but often overlooked reality. Many of the tools SMEs already use have AI built in.

They are just not using it.

That creates an immediate opportunity:

• Turn on AI features within existing software 
• Use natural language queries instead of manual reporting 
• Identify insights faster without additional investment 

These are quick wins, but they are only the beginning. The real differentiator is not access to technology, but how organisations use it.

Culture, not capability, determines success

If there was one theme that ran through the discussion, it was this: AI success is a leadership and culture challenge. Not a technical one.

Julie Holmes put it bluntly. “Leaders are not leading by example. They are leading by proclamation.”

In other words, businesses are telling teams to adopt AI without creating the conditions to make it happen. Two barriers stood out.

1. Lack of protected time

Teams are encouraged to learn and experiment with AI, but few are given the time to do it. Without space to explore, adoption remains superficial.

2. Leadership disconnect

If leaders are not actively using AI themselves, the signal is clear. This is optional, and in busy organisations, optional rarely becomes embedded.

Why most AI strategies never scale

Kunal Kaul reinforced the idea that technology is no longer the limiting factor. “The differentiator is the human system around it.”

That includes:

• Leadership mindset 
• Willingness to experiment 
• Openness to sharing data 
• Acceptance of failure 

AI development is inherently iterative. It requires testing, learning and refining. Without a culture that supports this, progress stalls.

Silos also play a critical role. When data is fragmented across teams, the intelligence generated by AI becomes fragmented too. The result is limited impact, even with advanced tools.

Cost saving is not the goal. Growth is.

Many SMEs begin their AI journey with cost reduction in mind. It is a logical starting point, but can also be a limiting one.

Kunal Kaul framed it clearly. “If we are settling for cost savings, we are playing defence.”

The real opportunity lies in using AI to:

• Create new products and services 
• Personalise customer experiences at scale 
• Deliver predictive support 
• Enter new markets 

Joe Seddon expanded on this idea, highlighting how AI is changing what is economically possible.

Problems that were once too complex or expensive to solve are now viable. For SMEs, this is a significant shift. It levels the playing field by:

• Smaller teams can tackle larger challenges 
• Bootstrapped businesses can compete with funded startups 
• Organisations can pivot faster when needed 

AI is not just improving efficiency; it is redefining ambition.

The cost of doing nothing is rising fast

One of the most striking insights from the panel was the idea of compounding risk. AI does not stand still.

Every month of inaction widens the gap between businesses that are experimenting and those that are not.

“The cost is not just doing something. It is the cost of not doing something.” This is where many organisations underestimate the impact. Delay is not neutral! It is an advantage handed to competitors.

Rethinking work: tasks, not jobs

Another practical way to approach AI came from Andrew Grill. Rather than thinking about roles, think about tasks.

Break your work down into:

• Tasks you enjoy and want to keep 
• Tasks that are repetitive or draining 

“Focus on what you love and automate the rest.” This approach removes fear and creates clarity. AI does not eliminate jobs. It redistributes work.

And when done well, it allows people to focus on higher-value activities.

Skills over tools with the shift to AI fluency

A recurring theme throughout the discussion was the importance of people.

Despite heavy investment in technology, most organisations are underinvesting in skills. Dave Birss highlighted a stark imbalance. The majority of spending is going into tools, while only a small fraction is going into people. This creates a disconnect.

Tools alone do not drive transformation. Skills do.

Kunal Kaul introduced a critical distinction. AI proficiency is not the same as AI fluency.

Fluency means:

• Understanding how AI impacts decisions 
• Knowing when to question outputs 
• Applying judgment alongside automation 

Without this, businesses risk creating a two-tier workforce. Those who can leverage AI, and those who cannot.

Why SMEs have the advantage

While large organisations often dominate headlines, the panel made one thing clear.

SMEs are better positioned to move quickly.

They have:

• Less legacy infrastructure 
• Faster decision-making 
• Greater flexibility 
• Higher tolerance for experimentation 

Joe Seddon described this as the beginning of an era where smaller, more agile businesses can compete at a much higher level. However, this advantage only exists if it is used.

Building a culture of experimentation

So how do businesses move from capability to culture?

Julie Holmes offered a simple but powerful framework. “Show and fail.”

Instead of focusing on polished success stories, teams should regularly share:

• What they tested 
• What worked 
• What did not 
• What they learned 

This creates:

• Psychological safety 
• Faster learning cycles 
• Greater engagement across teams 

And importantly, it normalises experimentation.

What customers actually care about

One final insight brought the conversation back to basics. Whether it is AI or human interaction, customers care about one thing. Outcome.

• They want problems solved quickly and effectively.
• Not perfect processes.
• Not impressive technology.
• Just results.

This shift is crucial when deciding where and how to deploy AI.

Where to focus next

To move from experimentation to impact, focus on the fundamentals.

Start here

• Audit the AI capabilities already in your existing tools 
• Invest in training and AI fluency across your team 
• Break workflows into tasks and identify automation opportunities 
• Encourage experimentation through regular sharing and feedback 
• Remove silos to unlock the full value of your data 

Then go further

• Shift focus from cost saving to growth opportunities 
• Reimagine products, services and customer experience 
• Build a culture where leadership actively participates 

The businesses that succeed will not be the ones with the best tools. They will be the ones who turn AI into a way of working.

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