Your organization has a reputation with AI. Do you know what it is?

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OPINION — Earlier this month, Gov. Gavin Newsom announced AskCA, a new AI tool built to help residents navigate state services, find jobs, start businesses and recover from disasters. Built by the Office of Data and Innovation, AskCA is now in pilot testing ahead of a public launch.

In June, the governor announced a first-of-its-kind partnership making AI available to every state agency, city and county. These announcements are just two examples of AI tools already helping California and assisting state workers as they serve residents.  

This adoption reaches well beyond government into business: As of April, 54% of employed Californians said they use AI tools at work at least sometimes. 

When Californians turn to these new advisers to understand an issue, industry or institution, they are seeking critical information. What is it telling them?

Most organizations don’t know. Many have typed their own name, their company, or an issue they care about into a chatbot. But a single response is an observation, not a broad gauge and few have checked what AI says consistently. Very few have acted on it. That gap matters more each month, as AI becomes a tool people use to make sense of policy debates and the organizations behind them.

What AI says is shaped by real inputs: the sources, the facts it draws on and how a question is phrased. These systems are constantly weighing new information and forming their best answer in the moment, so the picture a user gets today can look different next month as fresh material comes online.

That responsiveness is a strength, and it also means an organization’s story is never finished being told. The platforms themselves vary in what they draw on and prefer, reflecting each one’s own approach to sourcing and judgment rather than a single, fixed script.

For an organization, that variability is an opening. The version of an issue reaching a policymaker may not be the same based on sources searched, a competitor’s framing or a gap where its own position belongs. What a model says can change, because it responds to what’s accessible and well documented.

This is a dimension that can be measured and managed with the same rigor already applied to media coverage. There are tools and approaches that are moving quickly, and organizations that start paying attention now will have a head start on shaping how they’re understood.

Already there are AI tracking tools examining platforms over time and benchmarking results against competitors and opposing coalitions. The result is a clearer read on where an organization appears, how it is framed in contested territory, whether its position travels alongside controversy and whether the model gets its record right.

This isn’t a mention count. It’s a read on how an organization is characterized, favorably or otherwise, when the conversation turns to the issues that matter most to it.

New tools can audit how organizations are represented inside generative AI platforms, scoring things like discoverability, perception, accuracy and competitive positioning to produce a trackable reputation benchmark. 

Knowing the results is only half the job. The other half is improving them. Because these systems build answers from the sources they trust, the surest way to improve how an organization or issue is represented is to make sure accurate, accessible well-sourced information exists where models are most likely to go looking. The goal is to help these insights serve an organization well, by pairing what they surface with the judgment to know what it means and what to do next.

Sacramento’s newest policy adviser isn’t going anywhere, and its role in how California understands its policy debates, its institutions, and the people behind them will only grow.

The organizations and leaders who ask what that adviser is telling people, and act on the answer, will be the ones whose story is told accurately when it counts.

Patrick George is a partner at KP Public Affairs.