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Future Public Affairs Leadership in the AI Era

Session-20 The Leaders We Need Next.mp4 · 1:09:26 · 6 speakers

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Summary

The session examined how artificial intelligence is reshaping public affairs work and the leadership capabilities required for the next generation of professionals. Speaker 2 framed the central challenge as using AI to increase effectiveness and efficiency without allowing it to make public affairs professionals redundant.

Speaker 1 reported that Public Affairs Council surveys found AI use among public-affairs professionals rose from about 30% in 2024 to approximately 98% at the time of the session. Use remains concentrated in tactical work such as regulatory and legislative tracking, drafting and information retrieval; only about 7% of surveyed participants were using AI strategically. Speaker 1 cautioned that AI-enabled advocacy can inundate policymakers with content and produce a negative reaction to the profession.

The panel broadly agreed that AI can accelerate data collection, research, drafting, tracking and other routine work, but should not substitute for human judgment. Speaker 3 distinguished public administration, where AI could increase productivity and reduce discretion, from public policy, where human judgment is needed to identify fairness, accountability and public-interest issues. Speaker 1 similarly emphasized that healthcare applications require particular care because errors can have serious consequences for human health.

A core theme was that public affairs is fundamentally relationship- and trust-based. Speaker 1 and Speaker 2 argued that the function involves engaging stakeholders, interpreting local context, negotiating between business and the state, and forming narratives—not merely producing written briefs. Speaker 2 stated that AI creates time for more engagement with businesses, governments, central and state stakeholders, as well as internal functions such as R&D, CSR and ESG.

On leadership and talent, Speaker 3 said leaders should continue to identify raw talent through the quality of a person’s thinking, while using AI to remove routine work and operate at greater scale. Speaker 1 advised young professionals not to surrender their ability to think, challenge and question; the quality of AI output depends substantially on the clarity and rigor of the prompt and underlying thought process.

Speaker 1 identified discernment, empathy and courageous conversations as key leadership needs in an AI-enabled workplace. Speaker 1 argued that leaders should focus less on perfecting minor aspects of written work and more on enabling professionals to engage effectively with the public. The discussion also stressed that teamwork, interpersonal support and the human spirit remain differentiated capabilities that AI cannot replicate.

Audience questions covered AI’s possible impact on educational quality, the risk of an AI investment bubble, policy choices concerning children’s AI exposure, and how employers should assess emerging policy talent. The responses emphasized avoiding universal policy prescriptions across very different contexts, retaining traditional sources of information alongside AI, and assessing judgment, collaboration and the ability to ask for meaningful help—not only polished written outputs.

Key takeaways

AI adoption in public affairs was described as widespread, but strategic use remains limited relative to tactical use.
AI can improve research, drafting, tracking and scale, while human judgment remains essential for policy, ethics, context and stakeholder relationships.
Public affairs professionals should use AI as a tool rather than become dependent on it; curiosity, questioning and rigorous thinking remain critical.
Leadership in the AI era requires discernment, empathy, constructive handling of friction and the ability to develop people beyond technical output.
Future talent assessment should look beyond polished AI-assisted work toward judgment, contextual awareness, collaboration and help-seeking behavior.
AI policy and deployment should be shaped by local needs and context rather than imported wholesale from other jurisdictions.

Key moments

Session introduction
Speaker 1 introduces the discussion on reimagining public affairs and future leadership.
Moderator frames AI challenge
Speaker 2 sets out the two themes: AI’s impact on the function and leadership evolution.
AI adoption survey findings
Speaker 1 shares usage trends and warns about policymaker overload.
Human judgment in public policy
Speaker 3 distinguishes public administration from public policy and argues judgment remains human.
Leadership and raw talent
Speaker 3 argues AI should follow, not determine, human thinking and objectives.
Entry-level learning discussion
Speaker 1 advises young professionals to retain curiosity, rigor and independent thinking.
Definition of public affairs
Speaker 1 defines the profession as organized advocacy to deter harm or advance profit or purpose.
Audience Q&A begins
Audience raises concerns about AI, creativity and educational outcomes.
Context-specific AI policy
Speaker 1 rejects a universal approach to AI policy across schools and communities.
Closing reflection
Speaker 6 contrasts the positive future of public policy with uncertainty around public-policy jobs.

Decisions made

No explicit final decision was identified.

Proposals & suggestions (not confirmed decisions)

Leaders should assess team members partly by whether they can identify and request concrete, meaningful help, alongside their willingness to offer help. — suggested by Speaker 2. Outcome: Presented as a personal management practice; no formal decision.
AI policy for education should be decentralized and tailored to the needs, resources and realities of specific communities rather than made universal. — suggested by Speaker 1. Outcome: Supported by Speaker 3’s subsequent emphasis on context-specific policy thinking; no formal decision.
Leaders should use AI to remove routine work and enable professionals to engage more directly with stakeholders and public-facing work. — suggested by Speaker 1. Outcome: Consistent with the panel discussion; no formal decision.

Topics discussed

Opening: AI and the future public-affairs leader

to 00:06:00 Speaker 1, Speaker 2

Speaker 1 introduced a panel on reimagining public affairs and identifying the leaders needed for a changing environment. Speaker 2 framed the discussion around AI’s effect on public-affairs workflows and on leadership for AI-enabled professionals.

AI adoption, workflows and risks

to 00:09:04 Speaker 1, Speaker 2

Speaker 1 described rapidly increasing AI adoption, with use concentrated in regulatory tracking, legislative tracking, drafting and research. Speaker 1 warned that AI can also enable an excessive volume of advocacy and commentary directed at policymakers.

Human judgment versus automation in public policy

to 00:17:14 Speaker 1, Speaker 2, Speaker 3

Speaker 3 differentiated public administration from public policy, arguing AI can improve the former but cannot replace human judgment in the latter. Speaker 1 discussed the high stakes of healthcare, the limitations of incomplete AI-generated datasets and the enduring importance of human interaction.

Public affairs evolution and relationship-based work

to 00:23:58 Speaker 1, Speaker 2

Speaker 2 placed public affairs in the context of changing state-market relations and India’s growth ambitions. Speaker 2 argued that AI can take over trackers and mapping, while public-affairs professionals continue to negotiate, build trust and develop relationships.

Leadership, talent identification and scale

to 00:29:55 Speaker 2, Speaker 3

Speaker 3 said leaders should use AI after determining the objective, not allow it to determine the objective. Raw talent remains identifiable through thought quality, while AI enables higher productivity and work at greater scale.

Training and resilience for entry-level professionals

to 00:35:06 Speaker 1, Speaker 2

Speaker 1 said technological change is a transition rather than total human replacement. Young professionals should protect their capacity for thinking, questioning and challenging; good AI use requires precise, thoughtful inputs.

Changing leadership work and team culture

to 00:49:14 Speaker 1, Speaker 2

Speaker 2 described a shift from time spent on trackers and briefs to deeper engagement with business and government stakeholders. Speaker 1 defined public affairs as organized advocacy to prevent harm or advance profit or purpose, and called for discernment, empathy and courageous conversations in leadership.

Audience discussion: talent, AI risks and education policy

to 01:07:11 Speaker 1, Speaker 2, Speaker 3, Speaker 4, Speaker 5

Audience members raised questions about AI and creative thinking, a possible AI investment bubble, differentiated AI policy for children and schools, and the future assessment of public-policy talent. Panelists emphasized adaptability, context-specific policy, continued use of diverse information sources and assessment of human capabilities beyond written output.

Closing reflections

to 01:08:58 Speaker 1, Speaker 2, Speaker 6

Speaker 6 distinguished the promising future of public policy from the uncertain future of public-policy jobs. Speaker 6 urged attendees to consider whether their work adds value if it is readily replaceable by AI, then closed the session.

Important questions

How are government relations, legislative tracking, stakeholder mapping, drafting position papers and comment letters changing with AI, and what is a key risk? — asked by Speaker 2
Answered Speaker 1 said AI use has expanded strongly in tactical activities such as regulatory and legislative tracking, research and drafting. The stated risk was AI-enabled inundation of policymakers with advocacy, commentary and bill-related material, potentially causing an adverse reaction to the profession.
Which public-affairs tasks will become automated, and which will remain irreducibly human? — asked by Speaker 2
Answered Speaker 3 said AI could be highly useful in public administration, improving productivity and reducing discretion, while public policy still requires human judgment to identify issues of fairness, burden of proof and public interest. Speaker 1 added that healthcare requires especially careful human oversight and that public affairs remains dependent on human interaction.
What should the next generation of public-affairs professionals prepare for? — asked by Speaker 2
Answered Speaker 2 said AI can take over trackers and stakeholder mapping, but professionals will continue to negotiate and build trust-based relationships between business and the state.
How can leaders differentiate raw talent when AI makes work outputs look polished? — asked by Speaker 2
Answered Speaker 3 said leaders should continue to assess the quality of underlying thought processes and direction-setting. AI should support productivity after humans decide what needs to be done, and leaders should use that productivity to work at greater scale.
How can entry-level professionals develop resilience and muscle when AI shortens the learning cycle from flawed drafts and feedback? — asked by Speaker 2
Answered Speaker 1 advised young professionals not to let AI take away their power to think, challenge and question. Speaker 1 stated that effective prompting itself requires rigor, clarity and introspection, while technological change should be viewed as a transition to new work rather than total replacement.
How should leadership change when AI reduces routine work and can contribute to isolation from colleagues? — asked by Speaker 2
Answered Speaker 1 identified discernment, empathy and courageous conversations as leadership requirements. Speaker 1 said leaders should help professionals engage with the public and develop capacity beyond technical perfection, while recognizing that human friction and interaction cannot be removed from real-world outcomes.
Will AI worsen the gap between islands of excellence and oceans of mediocrity by reducing creative thinking among children? — asked by Speaker 4
Partially answered Speaker 1 did not accept the premise outright, but acknowledged AI will displace some parts of professional work. Speaker 1 argued that people will adapt and find new ways to retain valued aspects of work. Speaker 2 added that human spirit, team contribution and softer qualities may become more visible differentiators.
What happens if an AI investment bubble bursts, and what responsibility would the AI industry have to a generation encouraged to adapt education and careers around AI? — asked by Speaker 2
Partially answered Speaker 3 said speculation in new technologies is not unique to AI and suggested the investment question is primarily a financial-market and public-policy issue. The question of specific AI-industry responsibility to affected young people was not directly answered.
How should policy balance limiting AI exposure for younger children with using AI to address teacher shortages in rural schools? — asked by Speaker 5
Answered Speaker 1 said a universal policy would not fit contexts as different as a remote Indian village and New York City; policy should be based on the needs, resources and circumstances of each community. Speaker 3 reinforced the need to focus on the specific local problem rather than defaulting to foreign models.
How should employers assess emerging public-policy talent when information and work products are cheaper and faster to produce? — asked by Speaker 1
Answered Speaker 2 suggested assessing when people seek concrete, meaningful help as well as when they offer it. Speaker 1 said candidates should combine AI use with attention to wider signals from conversations, traditional media and news, keeping their eyes and ears open beyond AI-generated content.

Important numbers & facts

30% — Speaker 1 said about 30% of public-affairs professionals were using AI in the Public Affairs Council’s 2024 poll.
2024 — Year of the Public Affairs Council poll referenced by Speaker 1.
98% — Speaker 1 said current AI usage among surveyed public-affairs professionals was approximately 98%.
7% — Speaker 1 said only about 7% of participants were using AI for strategy or embedding it in strategic plans.
$70–80 per capita — Speaker 1 stated that India’s per-capita healthcare expenditure is almost close to $70–80.
$12,000 — Speaker 1 stated that the United States spends about $12,000 per capita on healthcare.
$8,000 — Speaker 1 stated that the United Kingdom spends about $8,000 per capita on healthcare.
Almost $900 — Speaker 1 stated that China spends almost $900 per capita on healthcare.
$4 trillion — Speaker 2 described India as a $4 trillion, fourth-largest economy.
6.8% growth — Speaker 2 referred to an expected growth rate of 6.8%.
2047 — Speaker 2 referred to the goal of Viksit Bharat by 2047, when India would be 100 years a republic.
$30 trillion economy — Speaker 2 referred to an ambition to become a $30 trillion economy by 2047.
6–8% growth — Speaker 2 said sustaining roughly 6–8% growth would be needed to reach the stated $30 trillion target.
22,000 people — Speaker 1 said a heavy-engineering industry where Speaker 1’s father worked had 22,000 people at peak production.
About 1,800 — Speaker 1 said the same heavy-engineering industry has about 1,800 people today.
1954 — Speaker 1 stated that the Public Affairs Council has existed since 1954.
43% — Speaker 1 cited a Kelly Monahan study stating that 43% of Gen Z do not want to be coached by their managers.

Speaker highlights

Speaker 1

Main points

Reported Public Affairs Council survey findings on AI adoption and strategic use.
Explained that AI is heavily used for tracking, drafting and research, but can create policymaker fatigue through AI-enabled advocacy volume.
Argued that AI should strengthen rather than replace public-affairs professionals’ ability to engage, advocate and influence outcomes.
Emphasized human interaction, contextual understanding, curiosity, questioning, empathy, discernment and courageous conversations.
Argued that policy should be adapted to local needs rather than transferred directly from other settings.

Positions

AI is a capability and tool, not a replacement for the purpose of public affairs.
Human interaction and engagement will remain central to public affairs.
Leaders should focus on developing people and outcomes rather than over-policing technical perfection in work products.
There should not be a universal policy approach to AI use in education across fundamentally different contexts.

Questions raised

What is public affairs, and how should professionals articulate its purpose?
How can leaders help AI-enabled teams retain human connection, motivation and collaboration?

Speaker 2

Main points

Moderated the session and structured it around AI’s impact on workflow and leadership.
Described AI as initially useful for drafting and synthesis, then increasingly capable of challenging arguments and generating concerns about job displacement.
Argued that trust, relationship building, negotiation and human spirit remain important differentiators.
Suggested that talent assessment can include whether individuals know when and how to ask for meaningful help.
Stated that leadership work is moving toward greater business integration and stakeholder engagement as AI reduces routine work.

Positions

AI should make public-affairs professionals more effective without rendering them redundant.
Reading and writing alone are no longer sufficient differentiators because AI can support both.
Team contribution, interpersonal conduct and the ability to seek help are meaningful forms of talent and leadership.

Questions raised

Which public-affairs tasks will be automated, and which will remain irreducibly human?
How should leaders distinguish talent when AI-assisted output is uniformly polished?
How should entry-level professionals develop resilience and learn from mistakes?
How can leaders preserve collaboration and motivation in a more AI-mediated workplace?

Speaker 3

Main points

Distinguished public administration from public policy in considering AI’s appropriate role.
Said AI could make administration more productive and reduce problematic discretion, but public policy requires human judgment.
Argued that AI should be used after humans determine the objective and direction of work.
Said AI can eliminate routine work and enable leaders and teams to operate at greater scale.
Characterized the AI investment-bubble issue as primarily a financial-market and public-policy matter, not an AI-specific question.

Positions

AI is useful in public administration but cannot currently replace human judgment in public policy.
The key leadership challenge is planning for scale, not merely completing individual tasks.
Future policy professionals should focus on the real problem in their context instead of over-relying on overseas examples.

Speaker 4

Main points

Asked whether widespread early AI use could worsen a perceived gap between excellence and mediocrity by weakening creative thought and independent problem-solving among children.

Questions raised

Will AI increase the perceived ‘oceans of mediocrity’ by reducing children’s creative thinking and independent problem-solving?

Speaker 5

Main points

Raised a question about balancing restricted AI exposure for younger children with the potential use of AI to address teacher shortages and absenteeism in rural schools.

Positions

Expressed a personal inclination toward limiting AI exposure for lower-grade children.

Questions raised

How should policy address unequal AI exposure between private premium schools and rural schools, while considering AI as a support for teacher shortages?

Speaker 6

Main points

Closed the session by separating the outlook for public policy from the outlook for public-policy jobs.
Said human interactions, judgment and decision-making suggest a strong future for public policy, while the job outlook is uncertain as AI agents may undertake some work.
Asked attendees to reflect on whether their roles add value if they are readily AI-replaceable.

Positions

The future of public policy is positive, but the future composition of public-policy jobs is uncertain.
Work that is easily AI-replaceable should prompt reflection on the value being added.

Questions raised

If a job is AI-replaceable, is the professional adding sufficient value, and why are they doing that work?

Follow-ups

Develop practical guidance for public-affairs teams on strategic, rather than solely tactical, use of AI.
Establish AI guardrails and verification practices, particularly for high-stakes domains such as healthcare and policy advocacy.
Review talent assessment and development approaches to place greater weight on judgment, contextual awareness, collaboration and the ability to seek meaningful help.
Consider locally tailored approaches to AI use in education, including the differing needs of lower-grade, private and rural-school settings.
Continue discussion on the impact of AI on public-policy employment and the value added by professionals in potentially automatable roles.