Balancing AI Innovation and Risk

Artificial intelligence (AI) presents a revolutionary opportunity for businesses, promising to streamline workflows, boost efficiency, and unlock new avenues for growth. However, navigating the landscape of AI also comes with inherent risks. As part of mitigating these risks, Responsible AI helps businesses maximise the benefits of AI technology while avoiding potential pitfalls.

The AI Return on Investment

Boards are focused on delivering measurable returns to fulfil shareholder interests. This is a general principle which applies to most commercial organisations. Where AI is concerned, there may be a gap in understanding between the ‘traditional’ board engagement with technology and the relationship with the returns. AI may be seen as a cost saving technology rather than one which delivers benefits beyond the short term maximisation of profit and cash. AI may be a smart business strategy, but AI strategy with governance is smarter. Here’s how:

Reduced Costs: AI can automate tasks, leading to significant cost savings in areas like data processing and customer service. Responsible AI ensures these savings are achieved without compromising fairness or transparency.
Enhanced Brand Reputation: Commercial supply chains are wary of companies seen as irresponsible with AI. They generally will avoid ‘designing-in’ technology which may attract additional downstream costs and liability which cannot be provisioned for, for example, the cost impact of correcting a biased system. By prioritising Responsible AI, businesses build trust and loyalty through the supply chain, leading to a competitive edge.
Mitigated Risks: Unforeseen bias and inaccuracy in AI algorithms can lead to costly legal battles and reputational damage. Responsible AI helps identify and address these risks proactively.

Addressing Boardroom Concerns

Due to the pressure on Boards to prioritise immediate cost reduction and return on investment, Responsible AI may be seen as a discretionary cost which the business can survive without. However, Responsible AI doesn’t have to come at the expense of efficiency. Here are some examples:

Define the purpose of the AI use throughout the business, undertake process value mapping, and set an AI policy.
Phased Implementation: Start with smaller, lower risk AI projects to demonstrate value and ROI before scaling up.
Focus on Measurable Benefits: Quantify the positive impact of AI governance initiatives, such as cost savings from reduced errors or increased employee engagement and wellbeing evidenced through reduced absence. Enable the engagement of talent otherwise restricted in the workplace due to bias and inaccessibility.
Align with Long-Term Vision: Frame Responsible AI as an investment in the company’s future, fostering trust and mitigating long-term risks.
Demonstrate Innovative Leadership by adopting AI strategy and governance to enhance design, de-risk design iterations, advanced manufacturing, digital twins and enhanced customer and employee experience through ‘gamification’.

Balancing Efficiency, Responsibility, Accountability and Ethics

Finding the right balance between efficiency and stakeholder considerations is crucial. Here are some strategies:

Prioritise Transparency and Explainability: Develop, procure or use AI systems that are clear in their decision-making processes, allowing for human oversight and intervention when necessary.
Promote Diversity and Inclusion: Become aware of the ‘echo chamber’ and build diverse teams that can identify potential biases in training data and algorithms.
Maintain Human Oversight: AI should be an augmentation to human decision-making, not a replacement. Humans should always be accountable for the final call. Introduce training to ensure leaders and teams know how to prompt AI effectively and interpret its outputs.
Become an educated Board fully aware of the AI risks and benefits and in doing so accept the accountability which accompanies power and responsibility.

Supporting the Business Case for AI

There are a number of research reports which have examined the relationship between business success and AI practice. We have selected a quote from a report produced by Accenture to provide an insight into their findings in this area:

‘Accenture¹ identified a small group (12%) of high-performing organizations which are using AI to create differentiated growth and outcomes. These “AI Achievers” are already generating 50% more revenue growth versus their peers (…) In an effort to understand what these Achievers are doing right, (…) among other success factors that have a combinatorial impact on business results, these Achievers are responsible by design. Achievers are, on average, up to 53% more likely than others to apply AI governance practices from the start, and at scale. We also learned that the share of companies’ revenue that is “AI-influenced” more than doubled between 2018 and 2021 and will likely triple by 2024″

Further Considerations

By adopting AI governance practices, businesses can unlock the transformative power of AI technology while minimising risks and maintaining stakeholder trust. Striking the right balance between efficiency, responsibility and ethics allows businesses to navigate the path to sustainable AI-powered success.

Anekanta® recommends that organisations commit to AI governance by creating their AI policy and AI Management System Implementation (BS ISO/IEC 42001).

Finally, there are legal and regulatory considerations to accommodate dependent on the regions where the business operates or uses AI decisions. Anekanta® guides your organisation through the entire journey including determining whether AI systems are in use, their risk category, EU AI Act compliance services, and a range of frameworks and services.

Note: AI Generated image. Request for a diverse boardroom table. First attempt showed one woman. This image is the second attempt and although appears diverse, the quality is highly questionable. It is shown here as an illustration of what an embedded AI content generator can do well and what its limitations are.

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Use of Generative AI: Generative AI tools may be utilised in research and drafting processes. All published materials are subject to substantive human review, professional judgment and oversight prior to release.

https://www.accenture.com/content/dam/accenture/final/a-com-migration/r3-3/pdf/pdf-179/accenture-responsible-by-design-report.pdf#zoom=40 ↩︎