Leadership Capabilities that SMEs need for AI Adoption

The 'what is technically possible' part of the AI adoption equation is full of genuinely significant opportunities. In one recent conversation with a client we discussed the very real potential of:

·      automating energy draining administrative workflows

·      moving from clunky reports to modern, beautiful dashboards

·      improving coordination and communications across the organization

·      giving everyone 24/7 access to an increasingly brilliant problem solving, planning and information gathering assistant

The gap between where the organization stands today and a future AI-enabled state where these dreams have become a reality isn't actually that wide. A glance at few YouTube videos will demonstrate that the destination is right over there — clearly visible and within grasp — just… on the other side of a minefield.

The material risk of making mistakes that cause harm to an organization's data, reputation, or operations is why most SMEs are moving slowly and playing it safe. This is why, among the SMEs we have surveyed to date, the actual application of AI is limited. For 20% to 30% of team members that are actually using AI tools somewhat regularly, usage for almost all of them stops at 'surface-level' tasks: touching up emails, summarizing large documents, or drafting social media copy.

The solution to this is not found in an AI strategy. It is not found in an AI platform or commercial licenses to frontier AI tools. It is found in the missing skills and experience at the leadership level that are required enable these things:

Technology modernization: the ongoing process of prioritizing and guiding technology investments and adoptions while balancing limited capacity for change to optimize how technology supports efficient operations and strategic goals.

Uncommon expertise required: solution architecture and integration planning; translating business needs into technical features; change and adoption.

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Data governance: the discipline of establishing and maintaining clear rules, roles, and processes that set standards for data quality across the organization, making your data useful for reporting, decision-making, automations, knowledge retention, and AI.

Uncommon expertise required: data strategy and modeling; understanding requirements for analytics, workflow automation, and integration.

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Cybersecurity: setting and governing clear, practical policies that people can understand and act upon to meaningfully reduce risk.

Uncommon expertise required: information security and enterprise architecture.

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AI piloting and adoption: establishing and overseeing balanced AI usage policies, helping leadership prioritize pilots based on feasibility and strategic importance, setting up pilots safely and securely.

Uncommon expertise required: detailed and up-to-date knowledge of AI capabilities, requirements and risks; innovation planning and leadership.

Two Questions for the Reader:
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1. Are technology modernization, data governance, cybersecurity, and AI piloting strategically important to your organization? Is it likely that these will help you achieve your goals, mitigate risk, manage your costs, retain and energize your people, and grow in a way that is both ambitious and sustainable?
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2. Do you currently have someone with all the skillsoutlined above providing leadership attention across all four of these domains?

This is, of course, usually answered in the sequence of "yes" and "no". These normally fall under the authority of a VP or C-level person who is mainly responsible for finance or operations. That person is usually talented, dedicated, and very busy carrying the heavy load of maintaining the foundations that keep the organization going.

This person is usually supported on the technology front by a Managed Service Provider (MSP). The role of the MSP is typically to make sure the internet works, people have secure and functioning computers, licenses are issued for core platforms, and helpdesk support is provided.

The MSP covers the ‘keeping the lights on’ scope of IT, but they are rarely designed to provide the strategic leadership required to drive data governance, evaluate AI risk, design a modern technology roadmap and guide innovative pilots.

These domains should not be left under-unattended in the way that they usually are. They are of high strategic importance. They are evolving at an extremely rapid pace. They are highly complex. And they involve high levels of risk.

The Solution Is Not Complicated

You do not need a full time VP of IT or Chief Information Officer to get this right. These are problems that do require skills and expertise. They do not necessarily require a great deal of time.

In our experience, most organizations can get the full level of skilled attention required to move meaningfully forward on technology modernization, data governance, cybersecurity, and AI piloting in as little as one or two days per week.

A fractional Senior Technology Advisor is an effective solution - an experienced technology leader who provides the strategic guidance, hands-on oversight, and domain expertise your organization needs on a part-time, flexible basis.

Typically this role will support the Operations or Finance leader who is accountable for the four domains we have discussed, giving them access to an expert navigator: someone who can see the minefield, who knows what might blow up (and how big the explosion will be), and who can guide the organization forward with both ambition and confidence.

If any of this resonates, we'd love to have a conversation.