The data and analytics space is in flux, and the pace of change is only accelerating. Over the next 12 months, I believe we’ll see shifts that not only change how teams operate, but also challenge the very identity of the profession. Some of these predictions might feel uncomfortable — but they’re worth thinking about.
1. The Disappearance of the “Traditional Data Analyst”
This may sound controversial, but the role of a traditional analyst who writes SQL, builds dashboards, and hands reports to the business is heading towards extinction. With LLMs already able to write and optimise SQL, generate dashboards, and even provide commentary, much of that work will be commoditised. Instead, analysts who survive will reinvent themselves as data strategists, product owners, or AI copilots, leaning into interpretation, judgment, and influence.
2. Smaller Firms Will Out-Innovate Big Consulting
Enterprises have long defaulted to the McKinseys and Accentures of the world. But in 12 months, I predict boutique ML/AI firms will dominate project-based work because:
They move faster than big consulting firms.
They offer specialists instead of generalists.
They don’t lock enterprises into bloated multi-year transformation contracts.
This is the classic “unbundling of consulting” — and it will hit the big players harder than most people expect.
3. AI Will Be Given Executive Authority
Here’s a provocative one: we’ll see the first AI-powered “executive” role in a large enterprise within the next year. Whether it’s an “AI CFO” managing treasury decisions or an “AI CMO” optimising marketing spend, boards will experiment with giving AI a defined slice of decision-making power. At first, it will be controversial, but as AI outperforms human decision-making in some areas (like forecasting or optimisation), this will accelerate.
4. Data Engineering Will Fragment
The golden age of centralised data engineering teams might be over. As AI-driven ETL/ELT tools and vector databases mature, data engineering won’t be the bottleneck it used to be. Business units will increasingly build their own pipelines and apps with AI assistance, bypassing the central team. The result: fewer centralised “data factories,” more federated and agile mini-teams.
5. Ethics and Regulation Will Divide Teams
Expect to see internal splits within data teams over how aggressively to adopt AI. Some will push for rapid implementation, while others will raise ethical, privacy, and bias concerns. This tension will create friction — and possibly lead to “shadow AI teams” inside enterprises, mirroring the shadow IT problem of the past decade.
6. SQL Will Become the New Excel
SQL won’t die, but it will be demoted. Just like Excel — still everywhere, still useful, but not the core differentiator of talent — SQL will shift from being a badge of technical expertise to just another tool everyone has access to. The new differentiator? AI prompt engineering blended with business storytelling.
7. The First AI-Only Analytics Team
Within 12 months, I predict at least one major enterprise will announce that it has no human analysts left in its core reporting function. Instead, humans will only audit outputs and focus on governance, while AI generates insights and distributes them autonomously. This will be celebrated as efficiency by some, and as a dangerous precedent by others.
Final ThoughT
In 12 months, data and analytics won’t just be “faster versions of today.” They’ll be redefined. Some roles will vanish, others will mutate, and entirely new ones will emerge. The controversial truth is:
Analysts who cling to SQL and dashboards as their core identity will struggle.
Organisations that rely on big consultancies will get outpaced by small, nimble AI boutiques.
And perhaps most unsettling — AI will increasingly stop being a tool we use and start becoming a partner we trust to make decisions.
Whether we embrace it or resist it, the next 12 months will mark a turning point.
