4 core AI principles that fuel transformation success

New projects can elicit a sense of trepidation from employees, and the overall culture into which change is introduced will reflect how that wariness is expressed and handled. But some common characteristics are central to AI transformation success. Here, in an extract from his book, AI for Business: A practical guide for business leaders to extract value from Artificial Intelligence, Peter Verster, founder of Northell Partners, a UK data and AI solutions consultancy, explains four of them.

Agility

Around 86% of software development companies are agile, and with good reason. Adopting an agile mindset and methodologies could give you an edge on your competitors, with companies that do seeing an average 60% growth in revenue and profit as a result. Our research has shown that agile companies are 43% more likely to succeed in their digital projects.

One reason implementing agile makes such a difference is the ability to fail fast. The agile mindset allows teams to push through setbacks and see failures as opportunities to learn, rather than reasons to stop. Agile teams have a resilience that’s critical to success when trying to build and implement AI solutions to problems.

Leaders who display this kind of perseverance are four times more likely to deliver their intended outcomes. Developing the determination to regroup and push ahead within leadership teams is considerably easier if they’re perceived as authentic in their commitment to embed AI into the company. Leaders can begin to eliminate roadblocks by listening to their teams and supporting them when issues or fears arise. That means proactively adapting when changes occur, whether this involves more delegation, bringing in external support, or reprioritizing resources.

This should start with commitment from the top to new ways of working, and an investment in skills, processes, and dedicated positions to scale agile behaviors. Using this approach should lead to change across the organization, with agile principles embedded into teams that then need to become used to working cross-functionally through sprints, rapid escalation, and a fail-fast-and-learn approach.

Trust

One thing we’ve discovered to be almost universally true is that AI transformation comes with a considerable amount of fear from the greater workforce, which can act as a barrier to wider adoption of AI technology. So it’s important to address colleagues’ concerns early in the process.