How Successful Organisations are Getting AI Right

Many organisations are investing in AI, but only a small group are getting AI right and seeing meaningful results. Research from a range of respected institutions, including Harvard, MIT, McKinsey and others, points to the same conclusion. The technology itself is rarely the obstacle. The real challenge is how organisations prepare for AI, structure around it and ultimately make it part of how they work.

In our work across sectors such as retail, travel, financial services and the public sector, we see the same patterns. The organisations that stand out are not those with the flashiest algorithms but those with the strongest foundations. They do a few things consistently well and it shows up in the outcomes they achieve.

The first characteristic is that they treat AI as a business priority rather than a technology experiment. High performing organisations do not start with models or platforms. They begin with clear business problems and a shared understanding of what outcomes matter. Leadership teams talk about AI in plain language. Managers understand the role it plays in their work. Frontline teams know what it is there to improve. This clarity makes adoption far easier and ensures that AI efforts remain grounded in value.

The second characteristic is the way they organise themselves. Success comes from the way teams are structured rather than the brilliance of any single technical specialist. MIT’s work on digital transformation reinforces this point. Organisations that make progress bring together commercial, operational and analytical expertise in focused teams with a clear remit. Ways of working become consistent. Accountability becomes shared. People feel part of something collective rather than recipients of something being “done to them”.

Trust is another essential ingredient. People will not use what they do not trust and trust does not come from technical detail. It grows when teams can see the logic behind a recommendation, when they have the chance to test and challenge it and when they experience small but visible wins early on. McKinsey’s global research highlights trust as one of the strongest predictors of successful AI adoption. Our experience supports this. The more open and collaborative the process, the more confident the organisation becomes.

Another defining behaviour is the discipline around measurement. Organisations that get real value from AI are very deliberate about defining success up front. They quantify time saved and revenue gained. They look at reductions in errors and improvements in customer experience. They revisit assumptions regularly and adjust course quickly when something is not working. This creates a culture of continuous learning rather than long and uncertain experiments.

Finally, the organisations that perform best manage AI as a portfolio of investments rather than a scattered collection of initiatives. They understand that some activities will be experimental, some will be incremental and some will have strategic importance. They keep a clear line of sight to business value and move resources to where they create the most benefit. They also stop things that are no longer adding value. This creates momentum and ensures that AI always remains connected to strategy rather than drifting off into isolated technical projects.

Taken together these characteristics form a pattern that cuts across industries and organisational types. The organisations that succeed are not the ones chasing complexity. They are the ones that build alignment across leadership, engage teams early and focus relentlessly on outcomes. AI does not deliver value because it is advanced. It delivers value when the organisation is ready for it.

At Beyond this is the core of our work. We help organisations create the clarity and discipline needed to turn AI ambition into practical, measurable progress. It is a very grounded approach with a simple intention. Make AI work in everyday operations and use it to improve decisions, service and performance. When the foundations are strong the technology finally has room to deliver.

If you are investing in AI but not yet seeing the results you expected, the answer is unlikely to be a more sophisticated model. It is almost always a matter of alignment, preparation and focus. The foundations matter more than anything else.