Safe AI adoption, from exposure to proof
Use AI confidently, and be able to prove it. ANG Associates helps mid-size and large companies protect confidential data and know-how while adopting AI, with services that answer the questions boards, auditors, insurers and customers ask.
It is "can we show that we control it, and are we moving fast enough?" Recent surveys point to a gap between how widely AI is used and how well leaders can prove it is under control.
of surveyed executives lack confidence they could pass an independent AI governance audit within 90 days
Grant Thornton, 2026 AI Impact Survey, 950 business leadersof surveyed CISOs say they can identify every AI agent in their environment
Okta-sponsored survey, 306 CISOs, July 2026of surveyed CEOs report no significant financial benefit from AI to date
PwC 29th Global CEO Survey, 4,454 CEOs, fielded autumn 2025These are self-reported surveys, and several were run or sponsored by firms that sell services in this area. Grant Thornton and Okta both do, and the PwC survey predates 2026. We use them as signals, not verdicts. Our related articles discuss each source in detail.
Each service stands alone and can be bought on its own. We suggest starting with the Exposure Check or Audit Readiness, then adding the others as your questions become specific.
Where is AI really being used in our company, and which confidential information is at risk?
CISO, General Counsel, R&D and business heads
If an auditor, insurer, customer or board member asked, could we prove that we control AI?
Board, CFO, CIO, General Counsel
Which AI agents can reach our data and systems, and who reviews that access?
CISO, COO, CIO
How do we move faster on AI without creating risk nobody has priced?
CEO, CIO, business leaders
If an AI system causes a loss, would our insurance actually respond?
CFO, General Counsel, risk managers
Which data and workloads must stay under our own control, and how do we get there?
CEO, CIO, General Counsel
Pharma combines valuable confidential data, validated systems and regulators who are writing their AI expectations now. That makes it hard to show that AI is under control, and it is why we position this offering with Life Sciences in mind. ANG Associates comes from Life Sciences and IT delivery, so we can work with R&D, Quality, IT and the board in one conversation.
EMA and FDA published ten guiding principles of good AI practice in drug development, covering the medicine lifecycle from early research and clinical trials to manufacturing and safety monitoring. They are broad guidance, not binding law.
EMA news release, 14 January 2026EU GMP Annex 22 on AI in manufacturing is, as far as we can tell, still a draft. As reported, it covers static, deterministic models and keeps generative AI and LLMs out of critical GMP uses. The final text may differ.
Pharmaceutical Technology, 2026 (trade press; check the EMA for the current text)of organizations surveyed across industries, not only pharma, said they lack automated controls that stop sensitive data leaking through AI tools. This is a vendor-run survey of 461 professionals.
Kiteworks survey, reported by Contract Pharma, July 2025The Kiteworks figure is cross-industry, vendor-run and from 2025, so we read it as a signal. Regulatory status changes; please verify against the EMA and your own regulatory team before relying on any of it.
Where do R&D, clinical and process data meet AI tools?
Discovery data, trial data, formulations and process know-how are the assets. We map where they reach public or unapproved AI tools, and which vendor terms and retention settings apply to them.
Can we show auditors and inspectors how our AI is controlled?
We prepare the evidence pack: AI inventory, intended use, risk classification, validation and change control records, monitoring and human oversight. This follows the direction of the EMA and FDA principles and draft Annex 22. We prepare you; we do not certify.
What can AI agents reach inside validated and regulated systems?
We review agent identities, permissions and logging around systems such as document management, quality, laboratory and ERP platforms, and how agent actions fit your data integrity and change control expectations.
Which AI use cases can go live now, and which need more control?
We sort your portfolio of use cases by risk, for example literature review, drafting support, deviation triage or commercial content. Low-risk cases move with guardrails; GxP-critical ones get the validation they need before they go live.
Do our policies respond when AI touches quality or safety decisions?
We prepare the questions and the AI use picture that your broker needs to review product liability, cyber and professional liability cover. We are not a broker and give no coverage opinions.
Where may our data and models live, and who can access them?
For clinical and patient-related data and cross-border transfers, we compare hosting and model options in Switzerland and the EU, and prepare the questions for your legal counsel and data protection officer.
We agree scope and deliverables before we start. Duration and fees depend on the size of your organization and the service you choose, and we set them out in a scoping call.
A short call to agree objectives, sponsors, the systems and business areas in scope, and what your board or auditors will ask for.
We build the inventory with your teams, classify each use by risk and data, and test current controls against the relevant framework.
You receive a ranked plan of gaps and actions. Decisions to fix, accept or transfer each risk are recorded with a named owner.
We assemble the evidence pack and board summary, rehearse the questions an independent reviewer would ask, and can support periodic review as tools and rules change.
Tell us which question your board, auditor, insurer or customers are asking. We will recommend the service that answers it and set out scope and deliverables.
Request a Scoping Call