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Governing AI: Board and Executive Oversight for Responsible Value Creation
AI Is Already Spreading Across Your Organization. The Question Is Whether Your Board Can Govern It Before You Lose Control - or Lose Ground?
Governing AI is a five-week online program that gives directors and senior executives a practical way to govern AI for responsible growth and competitive advantage - so you can move valuable initiatives forward without losing control of ownership, risk, or accountability. No technical expertise required.
AI Is Moving Faster Than Your Governance - and Every New Pilot Raises the Stakes
The board sees a polished demonstration. Management sees a promising pilot. Employees are experimenting. Vendors are embedding AI into products and processes.
But no one has a complete view of where AI is being used, where it is creating real value, who owns the outcome, or where the organization is exposed.
There is no shared view of value. Pilots move forward without clear criteria for deciding what should be funded, scaled, or stopped.
Ownership remains fragmented. Responsibility is divided across multiple teams, leaving no clear accountability for outcomes or failures.
The board lacks useful evidence. Technical demonstrations and long risk reports do not explain what decision is required or how success will be measured.
The boundaries keep shifting. Leaders have no consistent way to separate responsible experimentation from unacceptable risk.
Without clear governance, you can lose on both sides: waste capital and accumulate hidden risk while valuable AI initiatives stall and more confident competitors move ahead.
Govern AI With Enough Clarity to Move Faster - Not Just More Carefully
An AI briefing can raise awareness. A policy can restrict behavior. A risk register can record concerns. None of them alone gives the board a practical way to decide where AI should create value, who owns the outcome, or what evidence proves the organization remains in control.
Governing AI gives directors and senior executives a practical way to oversee value and risk together. It connects strategy, use-case choices, accountability, data, people, controls, and board reporting in one clear governance approach.
See the full AI portfolio. Move beyond isolated demonstrations to understand which uses matter, what they cost, who owns them, and where the risks sit.
Make stronger investment decisions. Apply shared criteria to scale, stop, or fund pilots based on strategic value and credible evidence.
Set ownership before problems surface. Clarify what the board must govern, what management must manage, and what technical experts must validate.
Create guardrails that support progress. Replace blanket restrictions with clear boundaries for responsible experimentation and value creation.
Give the board evidence it can use. Track value, risk indicators, human oversight, vendor and data controls, and workforce implications through a focused dashboard.
The result is a board and executive team that can challenge confidently, make explicit tradeoffs, and move valuable AI initiatives forward faster - knowing when the evidence says to scale, stop, or change course.
Build Your Governance Blueprint in Five Focused Weeks
This program is designed for leaders with full calendars and real decisions already in motion.
Five Online Modules
Spend approximately 30 to 40 minutes each week building the knowledge required for informed oversight.
Weekly Live Sessions
Use each 75-minute session to examine current cases and work through real governance questions.
Six Months of Updates
Receive a quarterly update brief as AI capabilities and risks continue to evolve.
Practical Tools
Apply the AI Governance Blueprint, board question bank, use-case portfolio matrix, risk and control checklist, roles template, board dashboard, policy starter, and 90-day action plan.
Two Application Paths
Follow the board or management path so each group can focus on its own decisions and clarify where board oversight ends and management responsibility begins.
Use One Practical Loop for Every AI Decision
The AI Governance Value Loop gives leaders a repeatable way to move from opportunity to evidence without losing sight of accountability.
Purpose. Clarify why AI matters to the organization and where it could create differentiated value.
Portfolio. Compare use cases and decide which initiatives to scale, stop, or fund.
People. Assign accountable owners and clarify decision rights across the enterprise.
Parameters. Set the ethical, risk, data, security, and human oversight boundaries for responsible use.
Proof. Demand evidence of business value and control effectiveness before confidence outruns reality.
Progress. Revisit decisions as the technology, risks, and needs of the business change.
Alongside the Value Loop, a second lens separates what the board must govern, what management must manage, and what technical experts must validate.
This Is for Leaders Accountable for Both Enterprise Value and Risk
This Is for You If:
You are a public- or private-company director, board chair, committee chair, CEO, general counsel, chief risk officer, CIO, CTO, or senior business leader.
Your organization is moving from isolated experimentation toward material AI adoption.
You lead an established or growth-stage organization in technology, manufacturing, financial or professional services, healthcare, consumer, or another data-rich sector.
You need to challenge AI decisions confidently without becoming a technical specialist.
You want innovation to move faster because ownership, evidence, and guardrails are clear.
You are willing to make explicit tradeoffs and govern AI as an evolving enterprise capability.
This Is NOT for You If:
You want a coding course or technical model-development program.
You are looking for legal advice or a static compliance certification.
You expect one AI expert, the CIO, legal, or the risk committee to own the issue for everyone else.
​You want a policy document without changing decisions, accountability, reporting, or operating practice.
Every New AI Pilot Raises the Cost of Getting the Next Decision Wrong
Each new pilot introduces more vendors, data, business processes, and ownership questions. Without shared criteria, AI activity expands while the board’s view of its value and exposure becomes increasingly fragmented.
Capital moves without enough evidence. More resources flow into pilots without clear measures for deciding what should be scaled, stopped, or funded.
Hidden risks become harder to contain. Unmonitored AI use can expose sensitive data, create biased outputs, and trigger regulatory, security, and reputational damage.
Competitive ground begins to slip. Unclear decisions slow valuable AI initiatives while more confident competitors continue building capability and experience.
One incident can trigger an overreaction. A preventable failure can push the board to restrict responsible uses that could have created meaningful value.
The longer these decisions remain disconnected, the more difficult and expensive they become to correct. Clear oversight protects enterprise value while giving responsible innovation room to move.
Improve the Questions Now and Build the Structure Within Five Weeks
Participants should improve the quality of their board and executive questions immediately. The program then turns that stronger dialogue into practical governance outputs.
Within five weeks. Draft an AI governance blueprint, assign decision rights, and define an initial board dashboard.
Within 60 to 90 days. A prioritized use-case portfolio and a basic policy and control structure can typically be established.
Over 6 to 18 months. Mature governance can become embedded in strategy, risk, talent, audit, and operating rhythms.
The goal is not to finish governance once. It is to give leaders a practical structure they can keep applying as AI and the business evolve.
Strong AI Governance Does Not Require the Board to Become Technical
Myth 1: “AI Governance Belongs to IT, Legal, or the Risk Committee.”
Truth: Those functions provide essential expertise, but the board and executive team remain accountable for enterprise value, risk, and the tradeoffs between them.
Myth 2: “The Board Needs Deep Technical Expertise Before It Can Govern AI.”
Truth: Directors need enough literacy to ask strong questions, test assumptions, demand evidence, and know when technical validation is required.
Myth 3: “A Policy and an Acceptable-Use Statement Equal Governance.”
Truth: A policy cannot decide which uses deserve investment, assign ownership, monitor value, or change what reaches the board.
Myth 4: “The Safest Choice Is to Wait Until the Technology and Regulation Settle.”
Truth: AI use is already entering organizations through employees, vendors, and pilots. Waiting can leave hidden use unmanaged while competitors build capability and experience.
Myth 5: “Every AI Pilot Is Strategic, or Every AI Use Is Dangerously High-Risk.”
Truth: A portfolio view lets leaders compare uses by value, exposure, and evidence so they can apply oversight in proportion to the decision.
​Myth 6: “Traditional Cyber and Model-Risk Controls Are Enough.”
Truth: Technical controls matter, but AI governance must also address people, processes, data, vendors, decision accountability, and human oversight.
Myth 7: “More Governance Will Only Slow AI Down.”
Truth: Unclear ownership, inconsistent approval, and undefined boundaries create friction. Right-sized governance helps valuable initiatives move faster because teams know who decides, what evidence is required, and where the boundaries are.
Myth 8: “We Already Have an AI Policy and Risk Process. We’re Covered.”
Truth: A policy or risk register is not enough if leadership still cannot see the portfolio, compare value, assign decision rights, or know what evidence should reach the board.
These directly reinforce gaps the client identified in approaches prospects have already tried.
Myth 9: “We Do Not Have Time for Another Long Executive Program.”
Truth: Each week combines approximately 30 to 40 minutes of self-paced learning with one 75-minute live application session focused on real governance decisions.
Jorge Titinger Brings Boardroom Judgment to AI Oversight
I’m Jorge Titinger, a former public-company CEO, experienced board chair and independent director, executive advisor, author, and speaker. Across more than 35 years in technology, semiconductors, turnarounds, transformation, and governance, I have led organizations through high-stakes change and worked with boards, executives, employees, customers, and investors when clarity and trusted commitments mattered most.
As a CEO, director, and chair, I have seen how the quality of a few critical conversations - and the decisions that follow - can determine whether an organization creates value or drifts. Today, I chair an ad hoc board-level AI working group and work directly with directors and executives to turn emerging technology into practical questions, clear accountability, and responsible action.
Experience Built for High-Stakes Decisions:
Public-company leadership. Former CEO of SGI and Verigy, where he led complex transformations and value-creation efforts.
Current board governance. Chairman of Axcelis Technologies, Lead Independent Director of Ichor Holdings, and Chair of the Nominating and Governance Committee at FormFactor.
AI oversight in practice. Chair of an ad hoc board-level AI working group and an active practitioner helping directors and executives govern emerging technology.
Recognized director expertise. NACD Certified Director, member of the NACD Nashville Chapter Advisory Board, and frequent NACD keynote speaker and panelist.
Author and executive advisor. Founder and CEO of Titinger Consulting, co-author of Differences That Make a Difference and The Real ROI, and author of The Beautiful Game of Leadership.
My mission is to help leaders and boards turn experience into practical judgment - and judgment into aligned, responsible action.
You Can Keep Reacting to AI Decisions or Start Leading Them With Clarity
The decisions made now will shape whether AI becomes a source of responsible growth or an expanding area of cost, confusion, and exposure.
OPTION 1: Keep Reacting One Pilot at a Time.
Allow decisions to remain fragmented across technology, legal, risk, HR, and business teams. Keep approving activity without a clear view of its value, ownership, or exposure - and wait for an incident to force action.
OPTION 2: Build a Clear, Repeatable Way to Lead AI.
Give your board and executive team the shared language, decision rights, practical tools, and evidence they need to move valuable initiatives forward while keeping the risks under control.
If you are ready to replace scattered decisions with clear oversight and responsible action, your next step is a focused conversation.
DISCLAIMER
Results may vary | Results are based on individual circumstances
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