Lynn Warneke writes about AI and digital governance, helping boards and business leaders think through technology risks, responsible adoption, data governance, procurement, and director education.
Lynn Warneke is most useful for board-level AI governance education and practical oversight framing.
Best for
A board advisory firm running a governance workshop on AI risk and director education.
Not for
An enterprise AI vendor seeking paid endorsement or sponsored posts to board buyers.
Key takeaways
Boards should own AI oversight, not leave it to IT.
AI ethics can guide decisions, but it cannot replace enforceable rules.
AI embedded in business software can make vendor lock-in a board risk.
Check first: Confirm scope, deliverable format, pricing, booking route, and whether they take structured engagements.
Main ideas
Boards should own AI oversight, not leave it to IT · AI ethics can guide decisions, but it cannot replace enforceable rules · AI embedded in business software can make vendor lock-in a board risk
Audience
4,853 LinkedIn followers · 7 Published posts reviewed
Lynn Warneke writes about AI and digital governance for boards and business leaders.
Their work turns responsible technology adoption into practical oversight concerns, including data quality, cybersecurity, procurement, vendor dependence, workforce capability and board expertise.
Follow their work for a board-level view of how technology choices affect risk, trust and business strategy.
Warneke connects broad principles to decisions directors and executives can act on.
Their AI governance post expands board oversight into eight priorities, from data foundations and guarded pilots to supplier contracts, workforce planning and sustainability.
Their post on AI and vendor dependence makes procurement a strategic governance issue: as AI becomes embedded in business systems and learns from company data, switching providers may become harder.
They also approach ethical principles with care, acknowledging that voluntary guidance can be vague or amount to ethics-washing while arguing it can still inform decisions alongside regulation.
Lynn Warneke’s posts treat AI and digital technology as board concerns, not just technical matters.
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The recurring thread is practical oversight: reliable data, responsible use, capable people, informed directors and careful supplier choices. They also stress that ethics frameworks help but cannot replace regulation, and that board diversity matters when different perspectives can influence decisions.
Boards should own AI oversight, not leave it to IT
Warneke turns broad governance guidance into board responsibilities: establish sound data practices, set guardrails for pilots, build responsible AI into company culture and ensure directors can oversee the risks.
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They add cybersecurity, supplier contracts, workforce planning and sustainability. AI oversight, they argue, involves the organisation’s risk culture and capability as well as its technology.
In a post on APRA’s position on generative AI experimentation, Warneke summarises four board actions from a Harvard Law School Forum article and adds four priorities of their own, including AI procurement, staff training and the energy and water demands of data processing.
AI ethics can guide decisions, but it cannot replace enforceable rules
Warneke acknowledges that voluntary ethics principles can be vague, difficult to apply and used for “ethics washing.”
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They see fairness, accountability, transparency and a human-centred, harm-minimising approach as useful lenses for procurement, risk assessment and implementation. They also argue that regulation is needed.
Writing about joining the Australian Computer Society’s AI Ethics Committee, Warneke describes ethical AI as one guardrail among others and calls for regulatory reform. In a separate review of Dominique Shelton Leipzig’s book, they highlight the distinct responsibilities of AI suppliers and deployers, as presented in the book.
AI embedded in business software can make vendor lock-in a board risk
Warneke extends the familiar concern about third-party cybersecurity risk to AI-enabled enterprise systems.
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When a company’s AI tools become closely tied to its data, policies and daily decisions, replacing a supplier can become costly and difficult. They argue that boards should treat procurement and supplier management as strategic governance questions, including how a company could exit a relationship.
Warneke describes AI being embedded in CRM, ERP and other platforms and trained on corporate data and intellectual property. They point readers to an AI procurement risk framework and a legal toolkit of AI contract clauses.
Data stewardship is a condition for responsible AI and trusted business
Warneke puts data quality near the start of the AI governance discussion: data should be accurate, legally sourced and maintained.
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In their review of Trust, they present author Dominique Shelton Leipzig’s argument that companies should recognise data as a valuable asset and connect data stewardship with privacy, legal compliance and business goals.
Warneke’s summary of the book highlights its proposed seven-step AI governance programme and board questions, alongside its discussion of data privacy, high-risk AI and supplier and deployer obligations.
Technology oversight depends on people and board composition
Warneke links technology education to organisational capability: skills in cybersecurity, data, AI and other emerging technologies need to be built across the workforce.
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They argue that boards also need enough digital understanding to oversee these issues. In their diversity writing, they endorse the importance of an inclusive culture and highlight research suggesting that multiple digitally skilled directors can contribute more than a lone specialist.
Warneke points to an Australian Computer Society podcast series on technology capability and, in a review of Akshaya Kamalnath’s The Corporate Diversity Jigsaw, connects inclusive culture and board diversity to digital oversight. They discuss the book’s diversity and critical-mass arguments alongside the research it cites.
What should a board do when a regulator says AI experimentation is acceptable?
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Start with a direct, prioritised board agenda that goes beyond general principles.
Lynn Warneke reports that Australia’s prudential regulator, APRA, broadly supports entities testing generative AI, particularly those with strong technology platforms and risk management, while advising weaker entities to proceed cautiously.
The post summarises a Harvard Law School Forum article’s four board actions: build a strong data foundation, support AI integration, embed responsible AI in company culture and improve board oversight.
It adds four priorities: extend cybersecurity to AI, strengthen AI procurement and supplier contracts, plan staff training and workforce transition, and include AI in sustainability strategies.
It also notes that AI demands board expertise and informed conversations about technology risk.
For brands planning a campaign
Use this as the spine of a governance workshop on AI risk: turn the eight priorities into discussion modules, board questions for management and a director education checklist.
Learn how embedded AI can create lock-in and which procurement safeguards to ask about.
Lynn Warneke argues that AI changes third-party risk.
As enterprise platforms embed AI and train on corporate data and IP, switching vendors becomes harder and incumbents gain leverage.
Procurement is therefore a governance issue, not just an IT purchasing decision.
The post points to a Risk Management Framework for Procuring AI Systems aligned with the NIST AI RMF and EU AI Act, and a Society for Computers and Law toolkit of AI contractual clauses.
For brands planning a campaign
Add procurement and vendor management to the workshop: contract clauses, exit planning, liability questions and board oversight of third-party AI risk.
Where should a director begin learning about AI governance?
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Explore a curated map of primary guidance, standards and ongoing sources.
Lynn Warneke shares a non-exhaustive list for non-executive directors seeking recommendations.
It includes AICD digital business and AI governance guides, GIA board guidance, Tech Policy Design Centre, OECD.AI, Australia’s AI Ethics Framework, Society for Computers & Law AI contractual clauses, cybersecurity guidance and standards such as ISO/IEC 42001 and the NIST AI Risk Management Framework.
It also lists podcasts, policy news, councils and institutes.
For brands planning a campaign
Use the list as pre-reading or a handout for a director education programme. In the workshop, identify which items need explanation or local adaptation.
How should a board use AI ethics without treating it as a slogan?
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Explore a practical, governance-focused view that pairs ethics with regulation and risk management.
Lynn Warneke announces an appointment to the AI Ethics Committee of the Australian Computer Society.
The post acknowledges criticism that voluntary ethical principles can be vague, hard to implement and vulnerable to “AI ethics washing.”
Warneke argues that an ethical AI approach—fairness, accountability, transparency, human-centred, rights-respecting and harms-minimising—remains an important organisational and board lens for procurement, risk assessment, development and implementation decisions.
They also say regulatory reform will be required.
For brands planning a campaign
The workshop can address ethics washing, how to apply ethical principles in procurement and risk assessment, and how ethics fits alongside legal and regulatory duties.
What connects data governance to AI governance and commercial value?
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See the board-level case for treating data as an asset and governance as a revenue enabler.
Lynn Warneke recommends “Trust” by Dominique Shelton Leipzig, calling it practical advice on why good data governance is good business.
The post highlights Leipzig’s argument that data should be recognised as a “pre-tangible” corporate asset, and that responsible AI, privacy and data leadership can drive revenue.
It covers the global legal landscape for data privacy, AI and cybersecurity, including the EU’s draft AI Act, high-risk AI applications, supplier and deployer obligations, a seven-step AI governance programme and board tips.
For brands planning a campaign
Use this in a data governance module, with board questions on data quality, privacy, AI supplier and deployer roles, and how governance supports rather than blocks innovation.
Why do director education and board composition matter for technology oversight?
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The post argues that one digital expert is not enough and inclusion determines whether diverse perspectives are used.
Lynn Warneke reviews “The Corporate Diversity Jigsaw” by Dr Akshaya Kamalnath.
The post argues that experiential and cognitive diversity matter alongside demographic diversity, but diversity initiatives deliver results only in an inclusive culture.
Warneke connects this to digital transformation and cybersecurity: boards increasingly need specialist technology expertise, and research suggests multiple digitally savvy directors—at least three—create the greatest benefit.
For brands planning a campaign
Treat director education as part of board capability and composition, not a one-off briefing. Discuss the critical mass of digital expertise, inclusive decision-making and how to assess a board’s technology fluency.
How does workforce capability connect to AI governance?
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Start here to see why director education and staff skills are part of the same adoption problem.
Lynn Warneke writes about the ACS Technical Advisory Board’s new podcast series on building workforce capability in cybersecurity, data, AI, and the Internet of Things.
They describe long involvement with the Australian Computer Society and a current role on its AI Ethics Committee, contributing to safe, responsible, and ethical AI adoption across Australian industry.
The post frames technology as the currency of the digital economy and asks how businesses can rapidly build the capabilities needed to thrive.
For brands planning a campaign
Extend the workshop beyond board oversight to capability building: what directors should know, what management should report, and how to sequence training and skills development.
AI procurement and third-party risk, including vendor lock-in3
Standards, guides and curated resource lists3
AI ethics frameworks and the regulation behind them2
Data governance and trust as a business asset2
Workforce capability and technology education2
Board ownership of AI governance1
Board diversity and critical mass of digital expertise1
Board ownership of AI governance
Warneke argues that AI oversight belongs to the board, not the IT function.
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In a post on APRA's position that entities with strong technology platforms and risk management track records are good candidates to experiment with generative AI, they condense a Harvard Law School Forum piece into four board duties: build a strong data foundation, sanction pilots within clear guardrails, embed responsible AI and an ethical risk culture from the top, and match board oversight to the expertise the topic requires.
They add four priorities they think the source leaves out: extend cybersecurity scope and practices to cover AI, tighten AI procurement and supplier contract management, sequence workforce training and transition planning, and include AI in sustainability strategy because data processing is energy and water intensive.
Their central point: good AI governance depends on capability, risk culture and data quality.
Turns third-party governance frameworks into numbered board actions, then extends the list rather than simply summarising it.
For brands planning a campaign
A strong hook for a governance workshop: the material reads like a board session outline, with questions directors should put to management and a gap list that can become workshop exercises.
AI ethics frameworks and the regulation behind them
Appointed to the AI Ethics Committee of the Australian Computer Society, Warneke states plainly that voluntary ethics principles are often vague and hard to operationalise or enforce, and that some companies engage in what critics call AI ethics washing.
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Even so, they argue that an ethical AI framework foregrounding fairness, accountability, transparency, human-centred design and harm minimisation gives organisations and boards a useful lens for procurement, risk assessment and implementation decisions.
They stress that ethics alone is not enough and regulatory reform is needed.
Their review of Dominique Shelton Leipzig's book Trust draws out the evolving global legal landscape on data privacy, AI and cybersecurity, including the EU AI Act, high-risk AI applications, and the separate legal obligations of AI suppliers and AI deployers.
Reads legal and governance texts for senior business audiences closely, then translates them into board-level decision lenses.
For brands planning a campaign
Supports a director-education session on where ethics frameworks end and legal duties begin, including the supplier-versus-deployer distinction boards are being asked to navigate without settled case law.
AI procurement and third-party risk, including vendor lock-in
The corpus's most distinctive argument is that AI embedded in enterprise platforms creates new forms of third-party risk, and vendor lock-in will be the sleeper risk of the digital era.
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Warneke notes that most businesses buy CRM, ERP, document and workforce systems from suppliers, then increasingly train them on corporate IP and data.
Once an AI assistant is woven into corporate decision architecture, the cost and failure rate of switching can make a replacement business case near-impossible to justify.
They connect this risk to procurement policy, contractual clauses and legal grey areas where supplier and deployer accountabilities are untested in court.
They also point to practical instruments, including a procurement risk management framework aligned with the NIST AI Risk Management Framework and the EU AI Act, and the Society for Computers and Law's AI contractual clauses.
Extends a familiar board concern—third-party cybersecurity exposure—to AI-embedded platforms, using a recognisable frame to explain an unfamiliar risk.
This is the one topic where Warneke makes an original claim rather than curating or explaining other people's frameworks.
For brands planning a campaign
A workshop module on AI procurement and supplier contracts would build on Warneke's existing argument, while the contractual-clause toolkit gives the session a concrete takeaway.
Warneke treats data quality as a precondition, not a parallel workstream: accurate, legally sourced and well-maintained data comes before effective AI use, and they list it first among board duties.
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In their review of Trust, they present Leipzig's case that data should be recognised as a pre-tangible corporate asset that boards account for even though it never appears on the balance sheet, and that companies frustrate their own digital transformation by neglecting stewardship and privacy responsibilities. The review highlights practical tools for directors, including a seven-step AI governance program and questions boards can ask management.
Reviews practitioner books and draws out board-facing components, such as governance programs and director question sets, rather than offering general summaries.
For brands planning a campaign
Offers a ready-made bridge between data governance hygiene and AI risk appetite, often where director audiences disengage.
Warneke argues that digital capability must span cybersecurity, data, AI, the Internet of Things and other emerging technologies, rather than focus on a single skill, and that this determines whether businesses can thrive in the digital future.
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They point to the Australian Computer Society's Technical Advisory Board podcast series as one contribution to workforce capability and describe their own involvement with the ACS as a member of its AI Ethics Committee. In their board governance writing, the same theme becomes a sequenced obligation: staff training in the short term, skill building in the medium term, and workforce transition planning in the long term.
Connects industry-body capability programs with board-level workforce planning, treating education as a governance commitment rather than a communications exercise.
For brands planning a campaign
Useful for framing a director-education program that extends beyond a single workshop and justifying a longer engagement sequence to a client.
Warneke publishes annotated, non-exhaustive resource lists for directors and invites readers to add their own.
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The lists group items into tools and resources, podcasts, news outlets, councils and institutes, and standards.
They include Australian governance guidance from the AICD and the Governance Institute, the OECD.AI Policy Observatory, Australia's AI Ethics Framework, the Society for Computers and Law contractual clauses, and standards and frameworks such as ISO/IEC 42001 and the NIST AI Risk Management Framework.
Their book reviews similarly surface components such as a seven-step AI governance program and board tips alongside the argument.
Curates and annotates other people's material, labels the list non-exhaustive and invites the audience to contribute recommendations.
For brands planning a campaign
Shows a format a partner can sponsor directly: a reading pack or toolkit commissioned for a client's board. It also shows Warneke is comfortable directing readers to named third-party resources rather than keeping everything on their own page.
Board diversity and critical mass of digital expertise
Warneke writes about gender diversity from several stated positions: as a woman in STEM, a hiring manager and leader, an advocate of tech diversity, and now from a board perspective.
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Reviewing Akshaya Kamalnath's The Corporate Diversity Jigsaw, they endorse the argument for experiential and cognitive diversity alongside demographic or identity diversity, and the claim that diversity initiatives deliver results only within an inclusive culture.
They add a governance point of their own: boards are bringing on non-executive directors with technology expertise, but research suggests the greatest benefit comes from having multiple digitally savvy members, around three.
Critical mass may therefore be a success factor alongside inclusive culture.
Draws on corporate law and governance scholarship to add a practical implication for board composition decisions that the source does not make directly.
The corpus’s only topic framed around board composition rather than AI risk, making it a natural fit for a director-education pitch about who sits on the board.
For brands planning a campaign
Extends the workshop offer beyond AI risk to board composition and skills-matrix design—often the entry point for a board advisory firm working with a client.
Lynn Warneke’s posts mention one organizational affiliation: membership on the ACS AI Ethics Committee.
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Other named organizations, books, and resources appear as recommendations, citations, or sources—not as stated brand relationships.
Australian Computer Society (ACS)
Disclosed partnership
Lynn Warneke says they serve on the ACS AI Ethics Committee, contributing to the safe, responsible, and ethical adoption of AI, and have been involved with the ACS for years.
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Ask whether the committee role is paid, voluntary, or employment.
Lynn Warneke writes about how boards should oversee AI and digital technology, and their posts work as a reading list for directors.
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The fastest way into their work is the curated guide to governance resources, standards and frameworks, which invites readers to add to it.
From there, the post on APRA's position on generative AI sets out eight board duties and shows their habit of extending someone else's framework instead of just summarising it.
Their most distinctive argument is about AI procurement: enterprise platforms with embedded AI trained on corporate data make vendor lock-in the sleeper third-party risk of the digital era.
Their book reviews of Trust and The Corporate Diversity Jigsaw show how they read governance material and what they take from it, including supplier-versus-deployer obligations and the case for several digitally skilled directors rather than one.
Read their work in that order: resources first, then the board-agenda posts, then the book reviews and diversity argument.
Both write for people who sit on or advise boards, and both explain what a board needs to be good at.
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Mehta makes the case for independent directors drawn from different professional backgrounds and for a resident director as a strategic governance asset rather than a statutory formality. Warneke argues that AI oversight requires board-level competence in data, ethics and procurement.
Mehta's posts are structured explainers on board roles and duties, written as general guidance without naming the sources behind the claims. Warneke reads one specific report or book, then adds numbered points of their own, as when they extend a four-part board AI framework with four further priorities.
Demirci works the trust-and-governance side of the same subject, writing about responsible AI, ISO 42001, the EU AI Act and whether protection of data and children should rest more on individual awareness or stronger regulation.
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Both treat AI governance as an organisational and societal question, not only a technical one.
Demirci's posts are conference takeaways and awareness commentary that end with a question to the audience. Warneke's read more like board briefings, naming frameworks, contractual tools and the untested legal boundary between AI suppliers and AI deployers.
Both analyse how AI redraws an industry's structure rather than reporting product news.
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Sinha argues that job boards, applicant tracking platforms and staffing agencies are collapsing into a single recruiting-as-a-service model delivered by AI agents, with humans where they add most value. Warneke argues that AI embedded in enterprise software changes how a board should assess supplier risk and exits.
Sinha's territory is talent acquisition, HR technology and the recruiting business itself, including a role transition and an open call for consulting work. Warneke focuses on governance, director education and AI risk.
For a board advisory firm weighing a governance workshop on AI risk and director education, Lynn Warneke's posts address the subject but do not establish audience fit.
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Their LinkedIn presence is small relative to most creator campaigns, with 4,853 followers in October 2026.
The posts cover AI governance, board oversight, data governance, procurement risk and director education, topics that align with the audience the client wants to reach.
But they provide no platform demographics, engagement figures or audience survey results to show followers' geography, seniority, occupation, employer type, or how many sit on boards or hold executive roles.
Treat the fit as plausible but unproven: the writing targets directors and senior business readers, but subject matter is not a measure of audience composition.
Before committing budget, ask for recent LinkedIn results for posts on AI governance or board education, including views, reactions and comment quality, and any audience information they hold: platform demographics covering geography, age and gender, plus a documented source or survey result for professional attributes such as director status or seniority.
LinkedIn followers
4,853
Follower count shown on the LinkedIn profile · 2026-10-10
Published posts reviewed
7
Full posts on AI ethics, board oversight, data governance, AI procurement, technology education and corporate diversity · 2024-07-29
Post publication window reviewed
November 2023 to July 2024
Earliest and latest publication dates among the reviewed posts · 2024-07-29
The seven LinkedIn posts document no sponsorship, advertising or brand-partnership formats for Lynn Warneke.
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They cover governance and technology: board oversight of AI, AI ethics committee work, data governance and procurement, book recommendations on corporate governance, and technology workforce capability.
None describes a media kit, rate card, sponsored-post format, newsletter placement, event appearance or other paid collaboration, and the posts publish no partnership inquiry route.
A brand interested in working with them on governance and AI-risk topics would need to ask directly about scope, format and terms.
Strong fit on subject matter and teaching content. The workshop does not depend on audience size, so the unmeasured audience is not a blocker. The constraint is commercial: no workshop format, pricing, lead time or booking route is published. Scope the engagement directly rather than buying from a menu.
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Brief
A corporate board advisory firm wants to run a governance workshop on AI risk and director education for client boards.
Reasons
The posts already read like board session material. Warneke takes APRA's stated position that entities with strong technology platforms and risk management records are good candidates to experiment with generative AI, condenses a Harvard Law School Forum piece into four board duties, then adds four of their own: extend cybersecurity to cover AI, tighten AI procurement and supplier contract management, sequence staff training and workforce transition planning, and put AI inside sustainability strategy. That eight-item list is workshop-ready in a way general 'AI for boards' material is not: each item is specific enough to argue about in a room.
Warneke covers the procurement layer that most board briefings skim. Their argument is that AI embedded in CRM, ERP, document and workforce platforms, trained on corporate data and IP, makes vendor switching progressively harder and gives incumbents durable leverage over buyers. Procurement, then, becomes a governance question, not just an IT purchasing one. They name practical instruments a session can walk through, including a procurement risk management framework aligned with the NIST AI Risk Management Framework and the EU AI Act, and the Society for Computers and Law's AI contractual clauses.
Warneke has already written the director questions. The post on APRA recommends the Harvard piece for its list of questions boards should put to management in each area, while their review of Dominique Shelton Leipzig's book Trust highlights a seven-step AI governance programme and board tips for the same audience. A workshop built on this material need not invent exercises from scratch.
Warneke addresses the objection that sinks a lot of ethics training. Announcing their appointment to the Australian Computer Society's AI Ethics Committee, they acknowledge that voluntary ethical principles are often vague, hard to operationalise and vulnerable to what critics call AI ethics washing. They argue that ethics remains a useful board lens for procurement, risk assessment and implementation decisions, while stating plainly that regulatory reform will also be needed. Directors who distrust ethics language are more likely to accept that framing than an unqualified one.
Warneke is comfortable pointing readers to other people's material. Their non-exhaustive resource list for non-executive directors gathers AICD digital business and AI governance guidance, Governance Institute board guidance, the OECD.AI Policy Observatory, Australia's AI Ethics Framework, cybersecurity guidance, and standards including ISO/IEC 42001 and the NIST AI Risk Management Framework. They invite readers to add their own. That gives a workshop credible pre-reading and a handout that is not self-promotional.
Conditions
Agree scope, deliverable format, pricing and booking directly; no published information specifies how a workshop would be delivered or what it costs.
Do not build the pitch around promotional reach. The only audience figure available is a LinkedIn follower count of 4,853. There are no demographics, engagement rates or evidence of how many followers hold board or executive roles, so promotion to a measured director audience is unproven.
Treat the absence of sponsorship documentation as an open question rather than a settled one: ask directly whether structured engagements of this kind are something Warneke takes on, and on what terms.
When to choose a specialist
Poor fit for two independent reasons. Commercially, no paid format is documented, so there is nothing to buy and no basis for pricing or measurement. Editorially, the endorsement would run against the clearest original argument in Warneke's published work.
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Brief
An enterprise AI vendor wants a paid endorsement: sponsored LinkedIn posts promoting its AI platform to board and executive buyers, with performance reported in reach and engagement.
Reasons
Across all seven posts, there is no media kit, rate card, sponsored-post format, disclosed paid partnership, newsletter placement or inquiry route. The posts are governance commentary, book reviews, curated resource lists and one appointment announcement. Ask directly whether Warneke accepts sponsored posts and, if so, what formats and terms are available.
Warneke's most distinctive piece of writing warns against exactly the products a platform vendor would want endorsed. They argue that as enterprise platforms embed AI and train on corporate data, vendor lock-in becomes the third-party 'sleeper' risk of the digital era, and that once an AI assistant is woven into corporate decision architecture, a replacement business case becomes near-impossible to justify. They frame procurement policy and supplier contract management as governance responsibilities and point readers to contractual-clause toolkits for buyers negotiating with vendors. Promoting one AI vendor to that same audience would directly contradict the position that built Warneke's credibility with it.
There is no performance evidence to assess a campaign against: the posts publish no engagement statistics, view counts, video or podcast performance data, comment-quality measures, audience demographics or survey results showing director or executive composition. A campaign that pays for reach and reports on it has no measurement basis here.
The format is unproven. The posts show sustained engagement with other people's books, frameworks and reports, not short-form promotional content built around a sponsor's product claims.
Alternative
If the aim is simply to reach boards with a governance message, commission an explainer or workshop module on procurement and lock-in risk rather than an endorsement, disclose the arrangement, and accept the editorial risk that Warneke's argument will not flatter any single vendor.
A worked campaign example
Angle
Position the workshop as 'what the board should actually ask about AI', using the eight priorities Warneke set out when APRA signalled support for generative AI experimentation. The session's spine: good AI governance comes down to capability, risk culture and data quality. Boards with strong platforms and track records can sanction pilots inside clear guardrails; weaker ones should hold back.
Deliverable
A three-hour session for one board, plus a director question pack for management and a one-page exit-planning checklist for the procurement module. Draw pre-reading from Warneke's own resource list, and flag separately the items a facilitator should explain or adapt for the client's sector rather than handing over a bare link list.
Modules
Opening: why this is board work. Warneke argues that AI oversight belongs with the board, not the IT function, and that boards need to consider what expertise they require at the table to have the right technology-risk conversations.
Data first. Accurate, legally sourced, well-maintained data is a precondition, not a parallel workstream. Draw on the argument that data should be treated as a pre-tangible corporate asset worth accounting for, even though it never appears on the balance sheet.
Pilots and guardrails. Explore what 'permission to pilot within clear guardrails' looks like in practice, including how the board sets the tone from the top on risk culture and ethical principles.
Procurement and lock-in. Examine embedded AI in enterprise platforms, how switching costs change the replacement business case, where supplier and deployer liability is untested, and what directors should ask about contract clauses and exit planning.
Ethics without ethics washing. Show how fairness, accountability, transparency and harm minimisation can guide procurement and implementation decisions, and where ethics ends and regulatory duty begins.
Capability and workforce. Sequence the obligations: staff training now, skill building next, workforce transition planning over the longer term. Boards may need multiple digitally savvy directors rather than one.
Next step
Use the module outline to ask directly about scope, format and terms; no published workshop product or booking route exists. If promotion to a director audience is in scope, request recent LinkedIn results for the AI governance and board education posts and any audience evidence held. If neither is available, keep the engagement to the workshop itself and leave promotion out of the brief.
Title
A half-day board workshop on AI risk, built from Warneke's own board agenda
Consider Filiz Demirci for the same board workshop on connecting responsible AI principles with practical organisational adoption.
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Reflecting on AI events, they link participatory ethics across the AI lifecycle with a practical warning: individual productivity gains do not necessarily create business value unless organisations redesign workflows. That pairing could help a workshop move from ethics concepts to questions about how AI changes work and how to assess results.
The posts focus on event takeaways and organisational transformation, not a director-specific agenda.
They offer no concrete board prompts on AI procurement, vendor lock-in, supplier contracts or board oversight.
The comparison draws on two posts associated with Demirci; confirm the account’s identity before proceeding.
Seven complete LinkedIn posts by Lynn Warneke cover board oversight of AI, AI ethics, AI procurement and third-party risk, data governance, curated governance resource lists, technology workforce capability and board diversity.
Posts from three other creators on board composition, AI governance and AI in recruiting provide similar-creator comparisons.
The posts carry no publication dates, so they describe positions that recur rather than a dated sequence of how those positions changed.
The posts cite the Harvard Law School Forum article on board governance of AI, Dominique Shelton Leipzig's Trust, Akshaya Kamalnath's The Corporate Diversity Jigsaw, the AICD, NIST, ISO and other guidance, and the ACS podcast series; these longer works are not available here, so they are described only as Warneke presents them, without a claim that they have been read.
LinkedIn shows 4,853 followers as of 10 October 2026; no engagement rates, audience demographics or performance data on video or podcast work are available.
The posts contain no media kit, rate card or sponsorship terms, so commercial formats are not documented in the posts here and should not be assumed to exist or not exist.
