Perhaps no innovation has greater potential to impact human history than AI. Regional governments and businesses have recognised this, and Saudi Arabia’s intention to establish a $40 billion fund dedicated to investing in AI advancement is just one proof of this.
As has been a precedent with tech trends in recent years, from 5G to cryptocurrencies, Middle Eastern countries aspire to be forerunners in the field. So, standing at the cusp of this revolution, regional business leaders must temper exuberance with a sense of responsibility. Sound considerations around preventing misuse must balance eagerness to innovate.
Tough questions demand answers if businesses are to address the ethical concerns surrounding AI. Thus far, public perceptions around AI in the Middle East have been largely positive — after all, the paradigm is projected to deliver benefits totalling $320 billion by 2030.
However, the shockwaves from the Google Gemini AI debacle should be a stark warning of how rapidly such sentiment can shift if the time to market takes priority over all else. Business leaders should, therefore, ignore the hype and instead focus on aligning AI’s vast capabilities with the needs of employees, customers, and business partners. Only then can AI be implemented meaningfully, ethically, and fairly to benefit and enrich every individual it touches.
It all starts with purpose. Here are some practical considerations for leaders who want to amplify AI’s benefits within their organisations.
Establish a purposeful vision for AI
The purpose is nothing without vision, and for AI implementations to successfully deliver their purpose, leaders must set an end destination, an ideal state. Build your strategic vision for AI with people in mind — in what ways will AI realistically help employees, customers, and partners?
Then, the necessary stakeholders from IT and other business functions will be involved in devising a realistic plan for achieving those goals. This sends out a strong message: AI is here to stay, and we’re committed to using it in a purposeful, governed, and accountable way.
To foster trust with employees, partners, and end customers, make this process as transparent and public as possible. For employees, this vision-setting serves to clarify AI’s role in the company—not to replace them and their colleagues but as a tool to augment and empower them to reach their goals.
For partners and customers, a purposeful AI vision is a roadmap that details how the business intends to use AI to elevate the quality of service offerings, tap into emerging opportunities, and protect the interests of everyone involved.
Build a robust and responsible AI governance practice
A strong hand is required to guide its purpose and ensure AI implementations remain on track. This role is best served by the principles of AI governance, which seek to proactively manage the risks involved in AI usage through sound policy, data frameworks, and usage best practices.
With a particular focus on empathy, transparency, and accountability, robust AI governance is the only way to keep businesses on the straight and narrow path of using AI to serve the interests of the collective public, not just business bottom lines.
Who’s in charge of AI governance? Typically, every individual involved in any shape or manner should be expected to uphold the principles of AI governance. Still, leadership and the board are especially accountable since they own the business vision for AI.
Duly executed AI governance doesn’t just prevent misalignment on AI implementations and purposes; it is also instrumental in keeping the business accountable for how things can be improved and done better if AI negatively impacts business employees or the customers they serve.
Take a second look at your data policies
It’s no secret that AI and data are highly interconnected. AI algorithms require a sizable amount of data to learn, improve, and generate more data that can be used to improve the algorithm further. In this closed cycle, the impact of certain decisions is more profound — feed AI with the right data, and it can generate accurate and equitable results. Feed it poor data, and the results are inaccuracy, bias, and opinions that may harm the business and its customers.
Data policies will have to be adjusted for this new paradigm. Emphasis should be placed on why certain data sets are connected to an AI solution — what business value and outcomes are expected from efforts to build the algorithm with this data?
Also, consider who decides what data to use, who gets access to the data that AI creates, and what their end goal is with that data. This level of scrutiny and transparency is needed to keep everyone accountable for the end purpose outlined in the business’ vision for AI and to minimise the long-term damage bad data decisions can cause to future AI implementations.
Finally, consistently discuss and assess the value of AI
Implementation is only the beginning. Keep AI initiatives aligned to their stated purposes by consistently evaluating, assessing, and optimising things over time. This is also an excellent opportunity to have honest conversations with users on the effectiveness of AI. For instance, dig deep into whether solutions like AIOps are truly alleviating the burden of critical but repetitive monitoring and remediation work for IT teams or how effective AI tools for HR are in reducing administrative burden or supporting talent recruitment and retention.
AI has vast possibilities, but only if leaders can set a clear purpose and path for its implementation now. Those who succeed will find that AI isn’t just any tool—it’s a tool that will empower their people, customers, and partners to realise their purpose and success wherever they are.
