Generative AI is predicted to have a huge impact on how we work. According to research by Accenture, three quarters of employees across the UK could see at least a third of their working hours influenced by GenAI, where their working patterns and behavior will make use of this technology. Yet, while there is a lot of discussion on how this technology might be used, there is no consensus on how well companies will apply this technology. In the same report, only 33 percent of those surveyed expect business leaders to be responsible when it comes to AI decisions and make the right choices to have a positive impact.
Why does this matter? Accenture estimates that not using AI – or using AI badly – could lead to an opportunity cost of £485 billion in economic value by 2038. This is a bigger opportunity for the UK than any other G7 country and it could almost double the UK’s long-term growth rate within 15 years.
Whether these figures are accurate or not, the overarching message is that using AI delivers more potential value than not using it. So how can we set the right strategy in place to take advantage of AI, and what kinds of choices will be involved?
Head of field engineering for EMEA at DataStax.
Strategies and priorities
GenAI is following on from other major technology trends and changes. From the move to client-server applications, through to the Internet, cloud and mobile, companies have gone through wholesale changes from new ways of working possible through to changing markets. For example, the switch from high-street shopping to online and mobile commerce affected many companies – some embraced online approaches, while others waited and saw their market share decline.
For GenAI, business leaders appear to be adopting one of three approaches – to Delegate to GenAI, to Accelerate with GenAI, and to Re-invent businesses on top of AI. Each of these has its own mindset and approach to business impact.
Delegate to GenAI
Using AI to delegate tasks concentrates on how GenAI can take over tasks currently performed by humans. GenAI replaces those people in their work, and staffing is then reduced as AI is brought in. The overall goal for this approach is to reduce bottom line costs to deliver a service to customers by a certain percentage – say 30 percent – and use this reduction to improve profitability.
Accelerate with GenAI
For the Acceleration approach, company leaders still look at GenAI to reduce human input and take over tasks. However, rather than immediately jettisoning those staff, companies can then look at how to redeploy those skills elsewhere. This approach uses AI to find more top line growth opportunities, improving productivity and profitability through more effective execution. Rather than taking a 30 percent reduction in costs, these businesses use that cash to power forward and increase their overall revenues and profitability together.
Reinvention
The third strategy – Reinvention – takes things further. While the Delegate and Accelerate strategies can be implemented by any business, the Reinvention approach is harder for well-established enterprises to adopt. It starts with the proverbial blank sheet of paper, and is based on asking the question, “How can I use this new technology to deliver that service better and more effectively than the traditional businesses that came before me?”
Rather than looking for cost savings or for more improvements in existing models, these companies look for completely new approaches to market that can deliver far greater results. Each new wave of technology has companies that are associated with them. For the Internet, the biggest example is Amazon, which used the online model to compete with bricks and mortar retailers. It is now worth $1.94 trillion, based on a combination of customer focus, competitive pricing and market expansion. Similarly, companies like Uber and Instagram built on mobile to create new apps that would fundamentally change the markets that they operate in, supporting millions of customers.
To reinvent an approach to business using GenAI, companies should not think about how to add AI to their existing application. Instead, the starting point has to be how to change the delivery of a product or service to meet a customer need, with GenAI at the heart of this approach.
The potential opportunities around Reinventing businesses is huge. Sonya Huang and Pat Grady of venture capital firm Sequoia point to AI – and agentic AI in particular – taking over services markets, rather than looking solely at the technology product sector associated with that service. Rather than Software as a Service, they term this “Service as a Software”. The goal for companies here is to dominate in markets that are far larger than software or technology alone, and that have previously relied on people and their skills. Rather than the $3billion market for AI software, companies should be looking at the $10trillion market for services.
In today’s world, the Reinvention approach involves looking at AI and then seeing how to structure a company, rather than the other way around.
Is your decision the right one?
Whatever your company, you will have to think about strategy and how to make the right choice around GenAI. You also have to be realistic about your goals, and how you can achieve them. It’s also important to note that many companies will change their approach to AI over time. Many CEOs and boards will decide that they want to create companies that follow the Accelerate path, but after some initial wins they will then retreat into the Delegate category.
On top of this, GenAI is still a nascent technology and companies are working out how they can scale up their projects. Approaches like retrieval augmented generation make it easier to embed company data into GenAI applications or services, but that data has to be good in the first place. According to Appen’s State of AI report for 2024, use of GenAI has gone up in businesses by 17 percent year on year, but there has also been a 10 percent annual increase in problems around projects due to data quality.
Without data, there is no AI. Without good data, there is no good AI deployment that can take over a role or deliver that performance improvement, let alone base an entire new company on. Understanding the whole approach around AI and data, and how these services work in practice, is necessary to achieve any strategic goals for the business.
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