Challenges and uses of AI in public affairs

In this edition of estrategIA, we welcome a special contribution from Gustavo Fedi, who offers his expert perspective on using AI in public affairs.

Artificial intelligence challenges professional structures and practices every day, and with increasing depth. From generating text and still images, it is now possible to create long videos, and the first film made entirely with artificial intelligence is even about to be released, giving rise to what some call AI-wood: a Terminator parody. But how does this affect public affairs and the representation of interests?

It is useful to distinguish GAI—generative artificial intelligence—from PAI, predictive artificial intelligence. The former, whose best-known examples might be ChatGPT and Midjourney, enables tasks to be automated and has caused an explosion in the production of written content and images. PAI, meanwhile, may hold greater appeal for professionals working to influence decision-making. Whereas GAI creates “new and original” content by learning from patterns and data structures, PAI enables forecasts and predictions about future events using current and historical data.

In other words, PAI uses machine learning to extrapolate the future, rather than to create content as GAI does. Although both use statistical analysis based on large volumes of data, algorithms and their interaction, one does so to “predict” which words, images and content belong together; the other to identify patterns and associate them with behaviours or phenomena that may occur in the future.

It is precisely this last point that is most interesting and challenging for professionals working in influence management, or public affairs.

Opportunities and challenges in public affairs¶

Public affairs is a professional field that draws on multiple disciplines to become more effective: law, political science, communication, marketing, digital strategies, public opinion research and more. All can contribute to informing decision-makers in order to represent a particular interest aligned with the common good.

In practice, it has three main objectives: establishing political relationships with influencers, decision-makers and regulators; managing issues within their regulatory and social contexts; and anticipating conflicts to prevent them through tactical or strategic action.

Until now, within the mix of methodology and insight employed by public affairs professionals—lobbyists—the ability to anticipate what might happen or how an individual or collective actor might respond, based on knowledge, experience and historical analysis, has been a distinctive asset in the market, beyond their network of contacts.

That is precisely why PAI could play a fundamental role for public affairs professionals, much more so than GAI, which helps them generate content or interact with audiences.

Alongside general regulatory challenges and fears that AI use could increase inequality, public affairs professionals face two related challenges: for PAI to work, it requires large volumes of data, integration and suitable software development, which is extremely costly; and how to construct robust, concrete KPIs—key performance indicators—and other measures when managing intangible assets.

This last point, along with rules governing the role and operation of those who seek to influence decision-making, is widely debated by professionals around the world. SEAP, the Society of European Affairs Professionals, for example, recently presented reports by Transparency International, which gathered information from 27 member countries on the state of transparency and access to public information in Europe. As for developing indicators, there is extensive debate and a strong desire to incorporate AI tools to build smarter, stronger KPIs that can communicate within companies the return on investment that public affairs generates from its budget. In other words, to measure the concrete impact of its work on the business. On measurement in public affairs, readers can consult the latest edition of the study by the Corporate Excellence foundation.

Uses and applications¶

Finally, some of the ways public affairs is using and implementing artificial intelligence at this early stage include:

1. Regulatory work: analysing legislation and case law to propose amendments or improvements to decision-makers.
2. Political analysis: anticipating or predicting the behaviour of decision-makers and public authorities, as well as organisations and social groups, through PAI.
3. Data-driven political decision-making: access to and processing of large volumes of information, including predictions, could enable decisions to take account of more factors, blind spots and implications of regulatory changes or measures than is currently possible.
4. Optimised stakeholder relationships: through greater access to data and the possibility of more interactions that are automated yet personalised.
5. Research and analysis: including the development of profiles of public officials, institutions, issues and other variables involved in understanding the context in which one operates.
6. Issue monitoring and crisis management: automation and unprecedented capacity to process and analyse large volumes of information allow better monitoring and detection of news and social media posts associated with an emerging issue.

Over the years, but above all through use and practice, more and better AI capabilities will increasingly be incorporated into public affairs. The challenge will be who leads the field, how they manage to implement it efficiently, and what other uses may emerge in future. What is clear at this point is that there is no time to lose: AI allows no respite, and it is always better to anticipate events than to rush to put out a crisis, as any lobbyist knows.

Gustavo Fedi

Senior adviser in public affairs and business development. Director of PAC Consulting.