AI unlock: Empowering future-ready analysts

Artificial intelligence is reshaping conversations about the future of work. In analytics, the prevailing narrative often drifts toward replacement: machines taking over tasks once done by humans. But the reality is different.

Analysts don’t see AI as a threat. They see it as a force multiplier—expanding their ability to drive strategy, retain top talent, and accelerate innovation, according to a survey of analysts conducted by dbt Labs in conjunction with The Harris Poll. Far from eliminating the role, AI is creating the conditions for analysts to step into more visible, more strategic, and more impactful positions inside their organizations.

Future-ready analysts

The new era of analytics will be conversational. Prompting is already replacing many manual tasks, multiplying analyst impact instead of diminishing it. Instead of spending hours writing SQL queries or building dashboards manually, analysts are increasingly guiding AI systems through natural language, defining questions, setting boundaries, and ensuring outputs align with business needs.

This shift is already reshaping collaboration. Analysts are no longer order-takers. They are becoming co-pilots in decision-making—sitting with stakeholders to explore scenarios in real time, pressure-testing assumptions, and helping leadership see risks and opportunities more clearly.

They’re also emerging as storytellers. With AI-assisted tools, analysts can craft narratives that combine structured data, qualitative signals, and forward-looking insights. This positions them not just as technical specialists, but as strategic advisors who bridge the gap between raw information and business outcomes.

In short, the modern analyst is a decision accelerator—someone who ensures that insight travels faster, with more accuracy and more context than ever before. But to reach this future, organizations must first remove the inefficiencies that dominate analysts' work today.

The AI unlock: From busywork to business impact

Despite these possibilities, the current reality for many analysts is less inspiring. Too often, they spend more time battling inefficiencies than delivering insight. Data validation, formatting, and error-checking consume valuable hours that could be spent on higher-order strategy. The result is unnecessary risk, slower delivery, and team burnout.

The appetite for change is overwhelming. According to a survey conducted by dbt Labs and The Harris Poll, over 90% of analysts:

• Want governed self-service platforms;
• Believe all-in-one solutions would increase productivity; and
• Say they’re more likely to stay with employers who invest in workflow optimization.

At the same time, 85% would consider leaving an employer that forces them to use outdated tools.

These statistics go beyond preference. They signal a profession on the cusp of transformation. Analysts want speed, but not at the expense of trust. They’re asking for structured, AI-powered environments where they can self-serve safely, collaborate effectively, and focus on strategy, not maintenance.

With capabilities like automated visualization, intelligent data cleaning, and real-time data quality detection, AI removes repetitive friction points. Instead of spending hours validating a dataset, analysts can guide decisions, monitor outcomes, and ensure insights are both explainable and actionable. This shift reclaims capacity that would otherwise be lost, redirecting it toward innovation and forward-looking analysis.

Balanced autonomy and governance

Outdated tooling isn’t just a workflow problem, it’s a retention risk. Ninety-four percent of analysts say access to self-service tools is a critical factor when evaluating employers. Losing top analysts means more than the cost of recruitment. It also erases institutional knowledge, complicates ongoing projects, and jeopardizes momentum on strategic initiatives.

Leaders often face a false choice: restrict access and slow analysts down, or open the floodgates and risk chaos. Neither approach is sustainable. The solution is balance: governed self-service that combines autonomy with oversight.

In practice, this means systems that provide audit trails, standardized definitions, role-based permissions, and clear lineage tracking. With these guardrails in place, analysts can explore data freely while leaders remain confident in the accuracy, security, and compliance of the insights being shared.

The benefits are tangible. Governed self-service eliminates tool sprawl, reduces redundant work, and ensures consistency across business functions. It accelerates collaboration, minimizes governance bottlenecks, and allows analysts to spend more time shaping outcomes.

Organizations that fail to invest in this balance risk more than inefficiency. They risk falling behind competitors who empower their analysts to move with speed, trust, and scale.

A C-suite imperative

For executives, the implications are clear: investing in AI and modern data platforms isn’t simply a technology decision. It’s a talent decision, a retention strategy, and a competitive imperative.

Companies that give their analysts modern, AI-powered environments enjoy higher morale, stronger retention, and more consistent insights. They also build organizations that can pivot quickly, seize opportunities sooner, and respond to market changes with greater confidence.

On the other hand, organizations that fail to evolve will see their most strategic minds trapped in manual workflows, unable to contribute at the pace the business demands. They’ll also face higher turnover, as analysts choose employers who empower them to do their best work.

The mandate for leaders is simple: empower analysts with AI-powered, governed workflows, or risk losing both talent and competitive ground.

AI-powered analytics doesn’t replace analysts—it elevates them. By embedding AI into governed workflows, organizations unlock the full potential of their data talent. The result is an analytics function that’s faster, more trusted, and more strategically central to the business than ever before.

These findings are just the beginning. Explore the full research in The Analyst Revolution.