Across the GCC, AI adoption is outpacing AI value. McKinsey reports that 84% of organizations have adopted AI in at least one business function, but only 31% have scaled or fully deployed it. Just 11% qualify as “value realizers”: organizations where scaled AI contributes at least 5% of earnings. For family businesses, this is a […]
Across the GCC, AI adoption is outpacing AI value. McKinsey reports that 84% of organizations have adopted AI in at least one business function, but only 31% have scaled or fully deployed it. Just 11% qualify as “value realizers”: organizations where scaled AI contributes at least 5% of earnings.
For family businesses, this is a trust paradox. AI could strengthen decision-making and competitiveness, yet poorly governed use can put reputation, sensitive information and family legacy at risk.
The solution is not to treat AI governance as a technical policy that lives with IT. It is to make it a leadership practice: clear decision rights, shared understanding of risk and visible accountability. Executive coaching can help family leaders turn governance principles into decisions and behaviours that hold up in practice.
Family enterprises have strengths that can support responsible AI adoption:
But these advantages do not remove the need for formal governance. In PwC’s 2025 Global Family Business Survey, only 9% of respondents had diverse boards and only 30% had a family constitution. These figures point to a potential gap between the influence family leaders hold and the structures that clarify how decisions are made.
A family firm needs an approach shaped around its ownership, operating model and succession priorities, not a generic corporate AI playbook. A focused AI strategy workshop can help a board and executive team agree where AI supports the family business strategy GCC leaders are pursuing, what risks are acceptable and who is accountable for decisions.
For background, see PwC’s 12th Global Family Business Survey 2025.
PwC’s survey reports that 74% of family-business respondents believe their businesses are more trusted. Yet the family-business trust advantage cited from Edelman has narrowed: from 16 percentage points in 2015 to 8 in 2025.
A strong name and history still matter. But trust is not a permanent inheritance. Customers, employees and partners increasingly judge a business by what it can do, and how responsibly it does it.
For AI, that means making trust visible through practical behaviours:
In family business governance, that visibility can help protect the reputation built across generations. Digital transformation leadership is not simply choosing technology; it is demonstrating that the business can adapt without compromising its values.
Coaching does not replace legal advice, cybersecurity controls or technical assurance. Its role is to help leaders align on governance and apply it consistently. Three coaching moves can help:
Bring family principals, board members, the CEO and relevant technology, risk and business leaders together to clarify:
Board education should give leaders enough AI fluency to ask informed questions about purpose, data, risk and value, without requiring them to become technical specialists. This is where AI for executives training and strategic leadership training can turn high-level concern into clear oversight.
Teams may already be using unsanctioned AI tools to draft, summarize or analyze work. A working session, not a blame-focused audit, can reveal what tools people use, what information they enter and what business need they are trying to meet.
IBM’s 2025 Cost of a Data Breach Report found that one in five breached organizations reported a breach involving shadow AI. Organizations with high levels of shadow AI had an average US$670,000 in additional breach costs compared with those reporting low or no shadow AI. The aim is to understand current behaviour, then give employees safe, approved ways to do useful work.
Family business succession planning increasingly involves preparing next-generation leaders to guide digital change as well as steward the company’s values. PwC’s 2025 survey highlights technology and digital transformation as leading priorities, with GenAI seen as a growth opportunity by 60% of respondents.
Use coaching to help current and future leaders discuss where AI can create value, what guardrails it needs and how the next generation can contribute to decisions. Make AI literacy a practical part of leadership development programs GCC businesses use for continuity and readiness.
Treat governance as a capability to build over time. Climb one rung per quarter, reviewing progress before moving on.
Agree why the business uses AI and connect that purpose to family values, strategy and risk appetite. Set boundaries for unacceptable uses.
Name the decision-makers, use-case owners and escalation routes. Document who approves, monitors and can pause an AI application.
Define approved tools, permitted data, access permissions and human-review requirements with the relevant technical and risk teams.
Create a cross-functional group to review pilots against their intended purpose, risk controls, business results and readiness to proceed.
Scale only when the use case meets agreed criteria for performance, security, adoption and value. Maintain monitoring and clear accountability after deployment.
Use the first quarter to establish a baseline and show whether leadership conversations are becoming operating practice. The indicators below are proposed measures, not industry benchmarks.
| Governance layer | Coaching focus | AI guardrail | Success indicator |
|---|---|---|---|
| Purpose and charter | Align leaders on value and risk appetite | Written principles and use-case boundaries | Charter reviewed by board or family council |
| Decision rights | Clarify ownership and escalation | Named accountable owner for each use case | Material use cases have documented approvals |
| Data and security | Surface current tool and data practices | Approved-tool and data-access rules | Shadow-AI conversations completed; actions recorded |
| Pilot review | Challenge assumptions and assess readiness | Human review and agreed stop conditions | Pilots reviewed against agreed criteria |
| Scale-up | Connect outcomes to business strategy | Ongoing monitoring and accountability | Scale decisions documented with evidence |
An AI strategy workshop can help the leadership team set the baseline, prioritize initial use cases and agree which measures matter to the business.
The cost is not only missed productivity or delayed transformation. IBM reports an average Middle East data-breach cost of US$7.29 million, compared with US$4.44 million globally in its 2025 report. Its findings also show that 63% of breached organizations had no AI governance policy or were still developing one.
Meanwhile, the GCC’s adoption-to-value gap remains significant: many organizations use AI, but far fewer have scaled it to material earnings impact. For family businesses, that gap is both a governance challenge and a competitive window.
PwC estimates AI could contribute over US$135.2 billion to Saudi Arabia’s economy in 2030-about 12.4% of GDP. Capturing that opportunity requires leaders who can move from experimentation to responsible execution, supported by clear oversight and capable teams.
Challenge your leadership team to take three steps:
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