THE BIG DEBATE
From AI experiment to everyday business value
For businesses wondering how to move from experimentation to meaningful AI adoption, Anne Kuhsiek, Partnerships Lead at AI adoption platform Pair, argues that the starting point should be a genuine workplace challenge- not the technology itself.
For many businesses, the question is no longer whether artificial intelligence will affect the way they operate. It is how to turn growing interest and experimentation into something useful, repeatable and commercially valuable.
Anne Kuhsiek, Partnerships Lead at AI adoption platform Pair, says businesses do not need to begin with an expensive or disruptive transformation programme.
“ The main thing I want businesses to leave with is a sense that AI adoption doesn’ t have to be a huge transformation programme,” she says.“ You can start small, identify the areas where AI can make a genuine difference to the work people are already doing, and build from there.
“ I’ d like people to come away with two or three practical things they can try immediately, but also an understanding that the bigger opportunity isn’ t simply learning how to use an AI tool. It’ s about developing the skills and confidence across the business to continually find better ways of working as the technology evolves.”
AI tools have already found their way into many workplaces, helping employees research information, summarise documents, prepare content and tackle administrative tasks. But adoption often varies considerably between people within the same organisation.
“ There are often people within a business already using tools like ChatGPT, Copilot or Claude and getting real value from them,” Kuhsiek says.“ The challenge is that this activity can be quite fragmented. One person might have transformed the way they approach a particular task while the person sitting next to them has barely used AI at all.
“ So the next phase is less about giving people access to AI and more about turning individual experimentation into repeatable ways of working that benefit the wider organisation.”
Start with the work
Rather than selecting a tool and then searching for ways to use it, Kuhsiek recommends beginning with the tasks employees already undertake.
“ Start with the work, not the technology,” she says.
“ Choose a handful of tasks that happen frequently and take meaningful amounts of time. That could be preparing for meetings, analysing documents, responding to enquiries, creating first drafts, researching prospects or summarising information.
“ Then experiment with how AI could improve those tasks and capture what works. If somebody discovers a really effective workflow, share it with the rest of the team rather than leaving that knowledge with one individual.”
Businesses should also decide how they will measure whether an experiment has delivered genuine value.
“ Finally, think about measurement from the beginning,” Kuhsiek says.“ It doesn’ t need to be complicated. Ask: did this save time, improve the quality of the output, allow us to do something we couldn’ t do before, or improve the experience for a customer? That starts to turn AI from an interesting experiment into a business investment.”
While efficiency may provide the most immediate return, Kuhsiek believes the bigger opportunity lies in using the time and capacity released by AI to support growth.
ANNE KUHSIEK
“ Efficiency gains still matter, of course,” she says.“ Saving time on research, analysis, sales preparation or administration can create a useful foundation. But the bigger opportunity comes when those gains are reinvested into growth: serving more customers, entering new markets, developing new services or giving employees more time to focus on higher-value work.
“ That is the distinction between AI hype and genuine transformation. The question is not simply,‘ How much time did we save?’ It is also,‘ What can the business now do that it couldn’ t do before?’”
Five practical steps towards AI adoption
1. Identify frequent tasks that consume significant employee time.
2. Choose a small number of genuine workplace challenges on which to experiment.
3. Record and share successful workflows across the organisation.
4. Measure whether AI saves time, improves quality or enables something new.
5. Use any efficiency gains to support growth, innovation and highervalue work.
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