The real technology challenge is execution, not adoption

As artificial intelligence tools become easier to acquire and deploy, building the governance, legal and commercial foundations needed to use technology effectively has become the central focus for businesses.

Nearly nine out of ten organisations in a recent survey by McKinsey and Company reported regular use of AI in at least one business function. Yet there is a persistent gap between its use and evidence of its value. For example, 44% of organisations report scaling AI across their enterprises, but only 37% attribute some enterprise-level earnings to AI.

From adoption to implementation

Despite this, the conversations businesses are having about AI have changed significantly.

A year ago, many businesses were asking what generative AI could do and whether they should experiment with it. Now, questions around AI are more practical and cover how AI should be deployed, what data could be used, who owns the outputs, how confidential information should be protected, and what happens when an AI-enabled process causes harm.

Answering these questions relies on reference to corporate governance, data protection, intellectual property, cybersecurity, contracts, employment, consumer protection, liability, and sector-specific regulations.

Decisions around cloud services, data infrastructure, and technology suppliers, which often intersect with those around the deployment of AI, introduce further considerations around outsourcing, security, data transfers, and contractual responsibility.

Clearly, the closer technology gets to the core operation of the business, the more important it becomes to ensure it is not managed as a standalone technology project. Its successful implementation requires legal, risk, compliance, cybersecurity, procurement, human resources, and business leadership to be involved from the start.

Governance must keep pace

Governance is essential once technology moves from experimentation into everyday use, especially as it often moves faster than formal decision-making structures.

For example, employees will not always wait for an enterprise-wide AI programme and will likely experiment with publicly available tools when the organisation has not yet provided access to approved ones. But an organisation cannot effectively manage technology that it does not know is being used.

A study of US companies by the National Association of Corporate Directors found that more than 60% were setting aside full-board time for AI, yet fewer than a quarter had audited where AI was used. Another study by EY found that even where formal AI governance policies existed, almost half of respondents said those processes were bypassed for urgent deployments.

More governance is not necessarily better, however, and poorly designed formal processes can become bottlenecks. Good governance processes will assist the business to use technology with greater confidence and consistency by establishing clear decision rights, responsibilities, and boundaries. This provides clarity over what can be approved, who should be involved, and how and when to escalate any issues.

Existing laws still apply

The absence of a dedicated AI law does not mean an absence of legal obligations. An AI application is subject to existing rules, including those governing personal information, intellectual property, contracting, confidentiality, employment, consumer rights, competition, cybersecurity, or sector regulations.

For businesses operating across African markets, the African Union's Continental AI Strategy provides a common direction for responsible AI development, but it is not a single AI law that applies uniformly across the continent.

National approaches differ, while existing laws already regulate many of the inputs and consequences of AI use. Businesses deploying the same AI service across several markets must consider:

• where the data will be processed;

• which entity controls it;

• what the technology provider could do with that information;

• whether the data can be transferred to another jurisdiction;

• what contractual protections are required; and

• what additional laws and requirements apply in that jurisdiction.

Execution creates the advantage

The focus on individual technologies sometimes distracts from the bigger task because AI depends on data, but data depends on effective compliance, management, and security. Its deployment depends on contracts, suppliers, people, and processes. Regional expansion introduces different legal and regulatory requirements. And every decision ultimately needs to support the organisation's commercial objectives.

As access to these technologies grow, businesses creating the most value aren’t being distinguished by the tools they use. Instead, they succeed by bringing together technology deployment, business strategy, good governance, and legal compliance early enough to be able to make good decisions and execute them well.

Bowmans X Tech

Bowmans has launched a new multi-disciplinary approach to digital innovation - Bowmans X Tech. It is designed to break down silos via a firm-wide approach to technology-related work in every sector. It brings together the right legal, sector, and market expertise around what each client wants to achieve – the client’s opportunity or challenge determines the team.

Pursuing a technology-related opportunity triggers multiple areas of law simultaneously, so the initiative uses the ‘X’ to reflect both the cross-practice and multi-disciplinary approach to delivering tech-related services across the full lifecycle of any initiative and to represent the multiplication of value that this enables for the firm's clients.

That strategic multiplication forms the foundation of sustainable growth