Most organisations have big ambitions for AI, yet many quietly admit they’re struggling to turn those ambitions into real outcomes, falling into the trap of unbalanced AI maturity and uncoordinated use – or artificial jagged intelligence.
While the technology is often seen as a panacea for every business challenge, there are important considerations before AI is considered as the solution, says Shabana Patel, head of data strategy and AI at Medihelp.
Patel is scheduled to present at the ITWeb Data Insights Summit 2026 on 12 February at The Forum in Bryanston, where she will unpack the "AI execution gap" that stymies the expected returns on AI investment.
“Businesses tend to consider AI as a solution to all their problems. Often there are other viable solutions, like process automation, which is simpler, with lower risk and cost. It’s important to understand what AI can do, at what level of accuracy, and if that outcome will address the business objective. The premature thinking is that it can be applied immediately to solve any problem. But this should be approached thoughtfully.”
By “thoughtfully”, Patel means business leaders must first identify the expected outcome, define what value looks like, and assess if AI is the right tool to achieve it.
“To support investment in AI, it is critical to ensure that the use case aligns with the business strategic objectives,” she continues. “Not every problem within the business justifies an AI investment. Having said that, the ones that do offer great returns on investment (ROI).”
Securing ROI from AI is a hot topic. Patel says there is a perception that AI will automatically generate an immediate fiscal return.
However, decision-makers must carefully weight the cost and risk against the potential outcomes.
Once the decision to proceed is made, the next question is: who is responsible for driving AI initiatives?
The issue of responsibility for AI integration remains a thorn in the side of many organisations.
Patel agrees that the boardroom conversation is often challenging, as scaling AI involves accountability across multiple business units.
“There has to be accountability and ownership of the AI initiative. It’s not just about a tool or simply delivering a module; there has to be consultation across the board to ensure adoption is being driven and that the approach is agile. This is simple once KPIs of the different executives align. It is a multi-disciplinary exercise,” adds Patel.
She says company culture heavily influences AI adoption and strategy.
The technology is perceived by some as a threat to their roles, leading to apprehension and misunderstanding. This highlights the urgent need for greater AI and data literacy.
“Accountability and trust are vital, but this cannot happen in siloes within the business. It must be embedded into operational decision workflows. Data and AI literacy is a reality; it is a must within organisations,” Patel adds.
At the ITWeb Data Insights Summit 2026, delegates will gain a grounded view of what it takes to deliver value at scale: from modernising architecture and strengthening governance, to enabling teams and building trust in AI-driven decisions.
The emphasis is simple: when strategy becomes actionable, people feel supported and value is prioritised… and AI becomes a catalyst for meaningful impact.
Topics include:
- How to prioritise AI and analytics initiatives that deliver tangible business impact.
- Insights into real-world blockers that derail data and AI strategies, and practical ways to address them across technology, people and process.
- A roadmap for moving from pilots to trusted, organisation-wide adoption using decision intelligence as the foundation.
Click here for more information and to register.
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