In the AI era, judgment is premium. CAOs need a new playbook.

Part 1 of a series on AI and Corporate Affairs, by Andrea Christianson, Partner, Penta Group and Russ Grote, Managing Director, KPMG US.

The responsibility of Corporate Affairs functions is rapidly expanding. Corporate Affairs Officers (CAO) are responsible – in whole or in part – for protecting and enhancing a firm’s brand and reputation among customers, employees, investors, policymakers, regulators, and a long tail of influential voices.

This responsibility comes amidst the fusion of internal and external communications and a continually evolving and fragmenting information landscape. As CAOs increasingly report directly to the CEO, they are also being asked not just for reputation management, but also for insights and strategic thinking to inform business strategy.

And now more advanced AI models, agents, and platforms present CAOs with the opportunity and challenge to transform their function to meet the moment.

Today, many organizations are well past using AI just for research, first drafts, and meeting notes. Teams are developing personas for leaders and audiences to refine messaging, agents for evaluating traditional communications products, AI-driven processes for deeper landscape analysis and predictive analytics, and content strategies for LLM consumption.

These efforts elevate the impact of an organization, but they are also best characterized as enhancements to existing workstreams.

They do not reflect true organizational transformation.

Why? These efforts swap out one constraint — time — for another constraint — judgment — creating new risks for Corporate Affairs functions to manage, which ultimately reduces the potential impact of AI on the function.

Corporate Affairs leaders need a new playbook for the AI era to meet the moment.

Today, Corporate Affairs functions solve for time through the pyramid-shaped org chart.

The org chart gives seasoned leaders more time to apply judgment at all levels. Corporate affairs leaders have time to develop big-picture strategy and inform reputation-shaping decisions, because mid-level leaders manage teams executing campaigns. Mid-level leaders have time to engage stakeholders and develop nested strategies to support those campaigns, because early career staff are conducting and synthesizing research and driving campaign tactics.

This model also supports ‘learning by doing’ as early career staff learn the craft through execution and mid-level managers gain experience in strategy. Knowledge from the top flows down, while knowledge at the ground level flows up.

The triangle-shaped org chart is a simple and sustainable solution to solving for time — and also supports enhancing judgment in the organization.

The problem: AI upends this time constraint. Initial research, analysis, planning, and drafts can be done in minutes. Reviews can be accelerated with AI agents.

The immediate temptation is to scale that efficiency against the ever-rising Corporate Affairs mandate.

However, if high-judgment people aren't pressure-testing the AI outputs, the increased content efficiency only increases the chance that it will land a team in hot water. AI may drive productivity gains in content creation, but it doesn’t generate more business leaders, lawyers, risk managers, and senior communication leaders to review.

Moreover, judgment is not best practices. It’s the application of firm strategy, competitive positioning, audience perceptions, media landscape insights, and future risks to an organization. It’s also the taste to understand what messaging, language and visuals will resonate, stick, and are consistent with a firm’s personality and ethos. It’s complex, and it evolves.

Without judgement, increased corporate affairs content risks merely proliferating undifferentiated (and frankly embarrassing) ‘AI slop.’

True AI transformation comes from scaling judgment.

In our view, used correctly, AI creates the possibility to scale the judgment of the Corporate Affairs function across their team – and also their firm -- enhancing the ability to reach and influence stakeholders.

Scaling judgment empowers the entire organization at all levels. Teams can pair their personal creativity, critical thinking, and collaboration with new AI capabilities to innovate and drive quality outcomes. Scaling judgment through AI transformation also reimagines how a CAO’s influence can reach further across their enterprise.

But how? The response we hear often is to put in more process, controls, and training to elevate the human-in-the-loop. However, this answer unwinds many of the productivity gains of AI. It also creates a top-down, process-laden hierarchy that snuffs out the entrepreneurial and creative zeal AI can also unleash, especially among highly talented staff.

In this series, we will walk through a different approach that includes:

1. Building a ‘knowledge layer’ that houses critical elements of judgment and a collaborative, transparent process to deepen and grow it over time.

2. Connecting the knowledge layer directly into AI agents, skills, and work products to scale that judgment throughout an organization in ways that both deliver efficiency through automation and elevate quality through coaching.

3. Reimagining new roles to transform and grow this new operating model, and the learning & development needs of people at all levels of their organization to actively participate in elevating the judgment of the function and leverage AI capabilities to expand their impact.

4. Cultivating a culture that treats AI transformation as an enabler of judgment and creativity, and not a replacement.