In the runaway train of AI development, those responsible for managing the risks are often chasing to stay ahead.
As stories of bots and AI tools gone rogue make headlines and consumer AI tools flood the market, public trust in conversational AI has taken a hit. A 2024 Gallup/Bentley University survey found only 23% of American consumers trust businesses to handle AI responsibly.
For professionals in AI governance and compliance, this is the reality they grapple with daily. With 2025 set to bring new challenges, from AI agents to fresh regulatory developments, we spoke to industry leaders to get their take on the future of AI governance.
The Regulatory Maze Will Become More Complex
In 2025, AI governance will heavily revolve around compliance with emerging regulations, predicts Michael Brent, Director of Responsible AI at Boston Consulting Group (BCG).
The EU AI Act, with its potential €35 million penalties, is set to become a defining force in global AI governance.
“The EU’s regulatory approach will serve as a closely watched test case, with organizations and nations monitoring its impact on competitive advantage and business operations,” explains Ms. Alyssa Lefaivre Škopac, Director of AI Trust and Safety at the Alberta Machine Intelligence Institute (Amii).
Ms. Lefaivre Škopac predicts that “soft law” mechanisms – including standards, certifications, a collaboration between national AI Safety Institutes, and domain-specific guidance – will play an increasingly important role in filling regulatory gaps. “It’s still going to be fragmented and won’t be fully harmonized for the foreseeable future, if ever,” she admits.
Meanwhile, the U.S. landscape is expected to remain fragmented.
Alexandra Robinson, who heads up the AI Governance and Cybersecurity Policy teams supporting U.S. federal government partners at Steampunk Inc., predicts that “state governments will invest in enacting consumer-focused AI legislation, while Congress is likely to prioritize reducing barriers to innovation—mirroring the landscape of U.S. consumer privacy regulation.”
Experts predict that the compliance landscape will take multiple shapes. Fion Lee-Madan, Co-Founder of Fairly AI, an AI governance software company, makes a bold forecast: “ISO/IEC 42001 certification will be the hottest ticket in 2025, as organizations shift from AI buzz to tackling real security and compliance requirements of AI responsibility. ‘’
Standards and certifications, though voluntary, are becoming essential tools for navigating the complex regulatory environment, with procurement teams increasingly demanding them to ensure trust and compliance from AI vendors, claims Ms. Lee-Madan.
Agentic AI Will Redefine Governance Priorities
While generative AI dominated headlines in 2024, experts believe 2025 belongs to “agentic AI.” These systems, capable of autonomously planning and executing tasks based on user-defined objectives, present unprecedented governance challenges.
“With the surge in research on agentic workflows, we anticipate an upsurge in AI governance centered around AI agents,” predicts Apoorva Kumar, CEO and Co-founder of Inspeq AI, a Responsible AI Operations Platform.
Building on this, Jose Belo, co-chair of the International Association of Privacy Professionals (IAPP) London Chapter, warns that the decision-making capabilities of these systems raise thorny questions about autonomy and the safeguards needed to prevent harm. Similarly, experts like Ms. Lefaivre Škopac from AMII anticipate significant research into balancing the autonomy of these systems with the accountability of their actions.
The workforce implications also loom large: “This will naturally intensify discussions and research around AI’s workforce impacts and replacing employees with AI agents and at what scale,” she cautions.
AI Governance Will Shift from Ethics to Operational Realities
“AI governance is no longer just an ethical afterthought; it’s becoming standard business practice,” notes Ms Lefaivre Škopac.
Companies are embedding responsible AI principles into their strategies, recognizing that governance involves people and processes as much as it involves the technology itself, according to Giovanni Leoni, Responsible AI Manager and Associate Director at Accenture.
Framing governance as part of a larger transformation, Mr. Leoni observes: “AI governance is a change management journey.” This shift reflects a growing recognition of AI governance as a critical component of strategic planning rather than an isolated initiative.
This evolution is further highlighted by Alice Thwaite, Head of Ethics at Omnicom Media Group UK, who points out that businesses are beginning to separate the concepts of AI governance, ethics, and compliance. “Each of these areas calls for unique frameworks and expertise,” she notes, reflecting a maturing understanding of AI’s challenges.
Meanwhile, Mr Kumar draws attention to the operational side of this transformation. With the rise of Responsible AI Operations (RAIops) and platforms like Inspeq AI, companies now have tools to measure, monitor, and audit their AI applications, integrating governance directly into their workflows.
Environmental Considerations Will Play a Bigger Role in AI Governance
Environmental considerations are becoming a core governance concern, experts predict. Mr. Belo of the IAPP emphasizes that reducing AI’s environmental impact is a shared responsibility between providers and deployers.
Providers must take the lead by designing energy-efficient systems and adopting transparent carbon reporting practices. Deployers, in turn, should embrace sustainable practices in cloud usage, prioritize greener data centers, and minimize redundancy. Ethical decommissioning of AI systems will also be crucial to prevent unnecessary environmental degradation.
Key Drivers of AI Governance Progress
What will drive progress in AI governance? Industry leaders offer key insights, each emphasizing different yet interconnected factors:
Michael Brent of BCG highlights the role of proactive corporate involvement: “The single biggest factor that will accelerate progress in AI governance is proactive corporate investment, including establishing Responsible AI teams.”
From a practical standpoint, Apoorva Kumar of Inspeq AI points to real-world consequences: “Loss of trust and reputation has already cost companies like DPD, Snapchat, and Google Gemini dearly. Ongoing failures will drive further progress in AI governance.”
On the enterprise front, Ms. Lefaivre Škopac stresses the importance of leveraging purchasing power: “Organizations must leverage their purchasing power to demand higher standards from AI providers, requiring transparency, documentation, and testing results.”
Lastly, as AI becomes more widespread, Mr. Belo underscores the need for education: “AI literacy is gaining recognition as a critical requirement across industries.”
Each perspective reinforces the notion that progress in AI governance requires action across multiple fronts—corporate commitment, transparency, and a growing focus on literacy and accountability.
The Road Ahead: Clear Challenges, Complex Solutions
In summary, the road to improved AI governance is unlikely to be straightforward. Some of the more optimistic predictions—such as increased investment in AI compliance—have been tempered by the ongoing complexities of both theoretical frameworks and operational challenges.
Global harmonization remains an elusive goal, particularly in light of recent developments in the United States. Organizations continue to grapple with a mix of “soft power” mechanisms—frameworks, standards, and protocols—without clear regulatory guidance for specific use cases.
At the same time, emerging AI trends, such as agentic AI, are poised to introduce a new wave of complex risks that will test the adaptability of responsible AI practitioners. A key distinction persists between a holistic, human-centered approach to responsible AI development and a narrower focus on risk management at the highest levels.
What’s clear is that no single team can tackle these challenges alone. As Ms. Robinson of Steampunk aptly summarizes: “My motto for 2025 is to move from extractive AI compliance to effective engagement. For those of us working on AI governance, we need to empower technologists to create and deploy secure, reliable, and responsible AI. This means meeting people where they are—we can’t hand a product owner a 500-question AI risk assessment and expect anything other than frustration.”
Although the AI governance landscape of 2025 promises to be as complex as ever, the contours of a more structured and actionable framework for AI governance are becoming visible.
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