Andy Clark, Tom Gough and Shailan Chudasama (both nursing colds) take on one of the most hyped topics in the industry: how the data and BI profession is changing, and how much of the AI noise is real.
Shailan starts by defining what they do today. BI delivery is still the core, but the role now spans architecture, stakeholder management and project delivery, with senior executives closely involved in the reporting. Clients increasingly want AI built in from the start, along with help training their own staff to use it well. Tom says the role is more complex at the senior level and more specialized at the junior level. Work that one person once did end to end is now split across business analysis, data engineering and modeling. His advice to newcomers is to specialize first, and data engineering has the biggest skills shortage, though also the steepest learning curve.
On AI, the hosts push back on inflated productivity claims. Tom warns that if people stop writing code, they lose the ability to review what AI produces, and unlike a human developer or vendor, there’s no redress when an AI gets it wrong. Andy argues that the skills now in demand are the ones the industry has always neglected: documentation and testing. Detailed documentation of the business problem gives AI something reliable to work from. Tom adds that clients are good at describing what they want but not what they need, and AI tends to agree rather than challenge, which keeps human judgment essential.
They also discuss a looming pipeline problem. If AI absorbs junior work, where will future seniors come from? And relying entirely on AI providers leaves firms exposed when heavily subsidized token prices go up.
Final thoughts:
- Tom: AI will be a big part of the future, but you still need people with senior skills who can describe the problem and direct the AI.
- Shailan: we’re now business consultants more than ever.
- Andy: AI projects are harder than people expect, so plan accordingly.
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