Imagine spending months developing an AI solution, investing significant time and money, only to conclude that the finished product is now obsolete.
That was the conclusion of a CIO presenting at a recent conference who described the output from their six-month investment as ‘brilliant, but useless’. So, what happened? Essentially, core AI capabilities progressed so far in those six months that what they were creating was now broadly available. While the learnings in those six months are valuable, we could consider it a missed opportunity cost for this organisation.
Unfortunately, for many technology leaders, this is becoming the reality. Organisations are investing heavily in building an AI capability but discovering that by the time their solution is ready, a comparable solution is available off the shelf.
AI is advancing faster than most organisations can make decisions, allocate investment and deliver change. Capabilities that once required significant development can become readily available products within months. Meanwhile, new start-up competitors are exploring the same opportunities, often without the constraints of established systems and processes.
Deciding how to make the right investments when the technology, economics and competitive landscape are constantly changing is becoming increasingly difficult.
Here, our Global SVP and Head of Data and AI, Richard Pugh, shares strategies that can help leaders know where to place their AI bets in this fast-changing landscape.
When AI moves faster than business decisions
There are three key developments that are currently shaping the AI landscape. First, AI systems can handle increasingly complex tasks. Second, they can operate for longer periods with less human intervention. Third, the economics of using these capabilities are changing as competition drives improvements in cost and performance.
Together, these shifts are expanding what's technically and commercially possible. But there's a fundamental difference between a capability becoming available and an organisation being able to benefit from it.
Businesses must assess opportunities, secure funding, manage risk, integrate technology, adapt processes and support employees through change. Each of these stages takes time, during which, the assumptions behind an investment may shift.
This creates a difficult tension for leaders. Move too quickly, and you risk committing resources to technology that may soon become cheaper or more widely available. Move too slowly, and competitors may turn those same advances into better customer experiences, more efficient operations or entirely new business models.
Instead of falling for either of these strategies, leaders should focus on being clearer about what the business is trying to achieve.
Start with ambition, not innovation
The constant stream of announcements and developments across AI news makes it tempting to react with new ideas for each new model or capability.
For business leaders, this is precisely the wrong starting point. Instead, organisations need a clear view of what they want to be known for and how they intend to compete. Each ambition creates a different lens through which to assess AI opportunities.
An organisation focused on service quality might prioritise capabilities that help employees resolve customer issues more effectively. One competing on operational efficiency might make different choices.
Both could use AI successfully, but their investment priorities should reflect their distinct business objectives.
The missing dimension in AI investment strategy: futility
Traditionally, organisations have evaluated technology investments through two important dimensions: impact and readiness.
Impact asks whether an opportunity could materially improve the outcomes the business cares about. Will it reduce costs, improve speed, strengthen margins or create new revenue?
Readiness asks whether the organisation can realistically deliver that value. Does it have the necessary data, technology, skills and ability to change how people work?
These remain essential considerations. But the speed of AI development introduces a third dimension that deserves equal attention: futility. This asks whether, if an investment promises significant impact and the organisation is ready to deliver it, is building that capability now still the right decision?
Of course, there will be opportunities where proprietary technology, unique data or differentiated processes create a compelling reason to invest. But leaders need to distinguish between capabilities that genuinely differentiate their business and those that are becoming increasingly commoditised.
Turning AI investment decisions into value
Organisations cannot control the pace of AI innovation, but they can influence the pace of their own decision-making and execution by ensuring their teams remain nimble.
Being nimble allows teams to make well-informed decisions at a pace that reflects the market, while ensuring the level of governance and oversight reflects the risk and impact of the decision. To do this, senior leaders must remain accountable for setting ambition, defining priorities and establishing the boundaries, but offer teams greater authority to evaluate opportunities to reduce unnecessary delays.
But as we’ve explored, speed alone isn't enough. Knowing when to invest is just as important as knowing where, and acting too early risks committing resources to capabilities that may soon become widely available.
Ultimately, making the right AI bets comes down to being clear about what you want to achieve, intentional about where and when you invest and nimble enough to turn those decisions into business value.
The organisations best placed to benefit won't necessarily be those investing in the most AI initiatives, but those that can make informed decisions and act while the opportunity still exists.
To see how Endava is putting this approach into practice, including rolling out AI tools to more than 7,000 employees across different business needs, read our article here.