February 2026
Artificial intelligence is no longer a future capability that sits neatly inside R&D or IT roadmaps. In life sciences—pharmaceuticals, consumer health, animal health, diagnostics, and beyond—AI is becoming the operating layer that touches discovery, development, manufacturing, market access, medical information, customer engagement, and even how regulators assess evidence.
That breadth is precisely why the corporate affairs function matters more than ever.
Life sciences operate under an implicit trust contract with society: a shared expectation that innovation, data use, and influence are exercised responsibly, transparently, and in the public interest. AI is rewriting that contract in real time.
And AI is doing it in a way that corporate affairs teams will recognize immediately:
- The pace of scrutiny is accelerating.
- The information environment is becoming more synthetic and more volatile.
- The expectations on transparency, governance, and ethics are hardening.
- The reputational consequences of small missteps are compounding globally.
This Confident View Ahead is written for corporate affairs leaders in industry who must both (1) support the business through an AI transition, and (2) modernize their own function so they can keep pace, stay credible, and create strategic advantage.
1. AI is shifting life sciences from “evidence generation” to “evidence engineering” across all market access areas
AI is increasingly used as a system-level capability to generate and analyze evidence across the full product lifecycle—nonclinical, clinical, HTAs, post-marketing, and manufacturing. That framing matters because it moves AI from “nice-to-have productivity” into “core scientific, regulatory, and access infrastructure.”
Regulators are already converging around what “good AI practice” should look like in drug development: human-centric design, risk-based validation, clear context of use, strong data governance, lifecycle management, and plain-language communication of limitations and performance. This is not abstract; it is quickly becoming the standard for credibility in submissions and public discussions about innovation.[6]
What this means for corporate affairs leaders
Corporate affairs must be able to translate a complex, technical AI-enabled evidence and access story into something that holds up under scrutiny from regulators, policymakers, investors, civil society, media, and employees—without overselling and being transparent about the limitations.
Practical moves
- Build an internal “AI evidence narrative” template: what AI is used for, what it is not used for, what guardrails exist, and how performance is monitored.
- Ensure “AI context of use” is consistent across functions, e.g., R&D, Quality, Regulatory, PV, Medical, and Commercial. [6]
- Decide now how you will address inevitable questions on bias, transparency, and accountability—before they arrive in a crisis.
2. Regulation is becoming AI-native, and corporate affairs will live on the front line
AI regulation is moving fast, and it is increasingly cross-cutting. In the EU, the AI Act establishes a risk-based framework and imposes obligations in phases, with the regulation generally applying from August 2026. [2] The European Commission’s own framing is precise: the AI Act is designed to address risks to health, safety, and fundamental rights and includes transparency requirements for certain systems (for example, informing users that they are interacting with a machine and labeling certain AI-generated content).[1]
In the US, the FDA has advanced draft guidance on the use of AI to support regulatory decision-making for drug and biological products (including a risk-based credibility assessment framework for an AI model in a defined “context of use”).[3] The FDA has also issued comprehensive draft guidance for AI-enabled medical devices across the total product lifecycle, addressing transparency and bias.[4]
In Europe, the EMA has expanded its public work on AI, including guiding principles for staff using large language models and an EU-wide effort to enable AI use while managing risks.[5]
The direction of travel is unambiguous: AI will be governed. Not in a single way, and not evenly across markets—but enough to make compliance, transparency, and stakeholder trust inseparable.
What this means for corporate affairs leaders
AI governance is not “someone else’s job.” Corporate affairs must help the business avoid a predictable trap: being technically compliant but publicly unprepared.
Practical moves
- Create a “regulatory plus reputation” AI map by market.
- Partner with Legal/Compliance and Regulatory to agree on a single external-facing position on AI.
- Build your strategic issues plans assuming regulations will tighten, not loosen.
3. AI ambiguity is a big corporate risk
In life sciences, the reputational failures that damage trust often share a pattern:
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- Stakeholders experience surprise (“We didn’t know you were doing that.”)
- They perceive power imbalance (“You used our data / our system / our vulnerability.”)
- They interpret silence as avoidance (“You won’t answer because it’s worse than we think.”)
AI intensifies this pattern because it can be simultaneously invisible, powerful, and hard to explain. If your company cannot clearly articulate the role AI plays in a patient journey, a consumer interaction, a trial design, or a pharmacovigilance signal-detection process, you have created ambiguity.
And ambiguity is where politicization, misinformation, and activism thrive.
What this means for corporate affairs leaders
Your job is to reduce ambiguity without creating false certainty.
Practical moves
- Establish a “minimum transparency standard” internally.
- Prepare an “AI misconceptions” FAQ for external stakeholders: what AI can’t do, what humans still do, what is monitored, what happens when models drift, and how performance is measured over time.[6]
- Align spokespeople.
4. Trust is under attack in a synthetic information environment
AI doesn’t just change your internal operations; it changes the environment you operate in.
Deepfakes, impersonation, synthetic media, and AI-generated misinformation are now mainstream business risks. Entrust’s 2025 Identity Fraud Report found deepfake attacks occurred roughly every five minutes in 2024, alongside a 244% YoY rise in digital document forgeries. Their report highlights how frequently deepfake attacks occur in digital identity contexts, illustrating the scale and speed of AI-enabled deception.[7]
For life sciences, the implications are specific:
- A fabricated “CEO statement” on product safety can travel globally before verification catches up.
- Synthetic “patient stories” or “adverse events” can be manufactured at scale to influence sentiment, regulators, or litigation narratives.
- Competitors, activists, or criminals can create convincing counterfeit content: websites, packaging, HCP letters, and medical guidance.
What this means for corporate affairs leaders
Your crisis playbooks must account for synthetic threats—and your monitoring must detect them early.
Practical moves
- Build a “synthetic media response protocol”.
- Upgrade social listening to include AI-enabled anomaly detection.
- Train executives and frontline communicators on impersonation risk.
5. AI is changing who influences health decisions, and corporate affairs must rethink engagement strategies
In pharmaceuticals and consumer health, influence is shifting:
- Digital tools and AI-assisted workflows increasingly support clinicians.
- Consumers are using AI-mediated channels for self-care decisions, symptom triage, and product comparison.
- Regulators themselves are building AI capacity and issuing guidance on safe use.[5]
- Global health organizations are actively addressing ethics and governance for emerging AI models in health contexts.[8]
This means corporate affairs teams can no longer treat “stakeholder engagement” as a linear trajectory. Engagement is becoming:
- more distributed,
- more real-time,
- and more shaped by platforms and tools outside your control.
See our ConfidentAccessTM solution, which can support this new era of planning.
What this means for corporate affairs leaders
You must engage as if your stakeholders have “AI copilots” sitting next to them, and sometimes making decisions for them.
Practical moves
- Rewrite your stakeholder engagement model for AI considerations: patient groups, HCP bodies, policymakers, data privacy advocates, cybersecurity actors, and technology ecosystems must be considered together.
- Build coalitions early; don’t wait until scrutiny arrives.
- Invest in health literacy. Your ability to explain AI plainly is now part of trust-building.[6]
