When you hear the term “AI governance,” what comes to mind?
Many SME owners might think, “Another new rule” or “This is for big corporations.” However, what I want to share here is the complete opposite.
AI governance holds the potential to become a “management compass” for SMEs to compete with larger companies.
AI Governance: Think “Design,” Not “Prohibition”
In November 2024, Lens Corporation launched “Lens Governance” (Sankei News, November 27, 2024). This service’s key feature is implementing AI governance in a way that connects the “first line” (frontline) and “second line” (management).
Why is this crucial for SMEs? Because many companies adopt a prohibition-based governance, telling employees “don’t use AI.”
In the SMEs I’ve supported, discussions about AI adoption often stall at the consideration stage due to concerns like “security risks” or “unclear legal liabilities.” This is a classic “all or nothing” mindset.
However, the essence of AI governance lies in designing “how to use” AI. Lens Governance’s approach hits this point exactly.
The Frontline-Management Disconnect Creates Risk
A common problem in many companies is the emergence of “shadow AI”—where frontline employees start using AI on their own, and management only finds out later. This is a textbook example of governance failure.
Lens Governance aims to create a system where frontline and management can view the same data, visualize AI usage, and assess risks. This promotes “appropriate use” rather than “prohibition.”
SMEs, in particular, should adopt this system. Unlike large corporations, they don’t have the luxury of dedicated AI governance staff. The system itself must be designed to handle governance.
Learning “Governance Evolution” from Wartime Ukraine
Another insightful news story is the case of Ukraine’s e-government (Nikkei, November 27, 2024). The fact that e-government usage reached 60% of the population amid war makes us rethink the essence of governance.
The Ukrainian government pursued “digital transparency” precisely because of the crisis. They deliberately visualized data and processes to reduce corruption risks and enable rapid decision-making.
This concept directly applies to SME AI governance. Precisely because of crisis situations (intensified competition, labor shortages, rising costs), companies should simultaneously pursue AI-driven efficiency and governance strengthening.
The Trinity of Data, Operations, and Governance
An ASCII.jp article (November 27, 2024) highlights a case where a domestic SaaS provider is implementing “core AI” on Oracle Cloud. The key point is that “data x operations x governance” becomes a competitive advantage.
Many SMEs suffer from a triple whammy: they have data but can’t use it, operations are person-dependent so AI yields little effect, and governance is merely a formality.
Achieving this trinity requires the following three steps.
3 Actions SME Owners Should Start Now
1. Create a “Whitelist” for AI Use
Instead of a “prohibition list,” create a “list of approved AI tools.” Evaluate them based on these criteria:
- Data handling (Is your company’s confidential information used for training?)
- Clarity of terms of service (Can contract terms be changed unilaterally?)
- Support system (Japanese language support, contact availability)
Start with about three tools and expand based on frontline feedback—that’s the realistic approach.
2. Share an “AI Use Decision Flow” Internally
Create a flow that allows frontline employees to decide for themselves whether they can use AI for a specific task. A simple flow like this is enough:
- Step 1: Is the data public? (Yes→OK, No→Go to Step 2)
- Step 2: Does it include personal or confidential information? (Yes→Requires approval, No→Go to Step 3)
- Step 3: Is there an expected productivity improvement of 20% or more? (Yes→OK, No→Consult)
With this flow, management doesn’t need to check every AI use. It encourages autonomous decision-making on the frontline while managing risk.
3. Make AI Governance a “Management Meeting Agenda Item”
Create a system to report AI usage and risk assessments at monthly management meetings. Be sure to check these three points:
- Status of new AI tool adoption and their purpose
- Any incidents (data leaks or malfunctions)
- Improvement requests from the frontline
This habit transforms AI governance from a “rule on paper” into a “living management tool.”
Common Failure Patterns and How to Avoid Them
A common failure I see in consulting is trying to confine AI governance to just the “IT department” or “legal department.”
AI governance is an intersection of management strategy, HR evaluation, risk management, compliance, and information security. No single department can cover it all.
That’s why it’s crucial for “the owner to take the lead.” Send a top-down message that “AI is not prohibited, but to be used appropriately,” and form a cross-departmental project team. This is the key to success.
Conclusion: AI Governance as an “Offensive” Management Tool, Not a “Defensive” One
Whether you view AI governance as a “bothersome rule” or a “source of competitive advantage” will determine the fate of SMEs going forward.
Services like Lens Governance embody this way of thinking. As the Ukraine case shows, it’s precisely in times of crisis that governance should evolve. That decision will impact a company’s survival and growth.
Why not add “How to design AI governance” to your management meeting agenda starting today? The first step begins with just a 30-minute discussion.
References:
- Sankei News: “AI Governance as a Management Compass: Launch of ‘Lens Governance’ Connecting First and Second Lines” (November 27, 2024)
- Nikkei: “Ukraine’s E-Government Usage Reaches 60% of Population, Functioning Amid War” (November 27, 2024)
- ASCII.jp: “Domestic SaaS Provider Advances ‘Core AI’ Implementation on Oracle Cloud: Data x Operations x Governance as Competitive Advantage” (November 27, 2024)
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