COMMENT
Artificial Intelligence (AI): Not since the invention of the operating system have we seen a technology poised to have such a far-reaching impact on the way we work and live. And organizations are eager to get in on the action. In fact, according to a recent studies From Avanade, where we surveyed more than 3,000 business and IT executives globally, 92% of respondents agreed that their organization must transition to an AI-focused operating model this year to remain competitive.
But instead of shifts, I see sprints. Many organizations are reacting to the hype, rushing to satisfy board curiosity and implementing AI somewhere (everywhere) to select a box. They often anticipate the important, hard work of finding the right problem for the technology (whether it’s a new revenue stream, increased profitability, process optimization, or cost savings), understanding their AI readiness, and designing a road map that corresponds to it.
The wider tech sector also has an important but tough job to do, ensuring we lead by example and design and apply AI responsibly. After all, just because we can use AI for everything doesn’t mean we should.
Bridging the gap, mitigating bias, and more
So, as we all absorb the mania we’ve been exposed to in 2023, I recommend that individuals, organizations, and the entire tech industry focus on these five priorities in 2024.
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Bridging the gap between AI advances and government regulations. Even though the US government and the European Union have announced it policies on the use of artificial intelligence, we still live in a Wild West type structure. Advances in the application of artificial intelligence will require access to tons of data, and this will clash with privacy concerns. Yet we must address the question of how to maintain privacy in a way that still allows innovation. I believe there is a huge opportunity for technology companies to do what matters and step up to invest in privacy-preserving technologies.
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Mitigate bias and ensure ethical use. Mitigating bias in AI is essential for fairness and equality partial systems can perpetuate social inequalities. Accurate and reliable results depend on unbiased AI, especially in critical applications like law enforcement and hiring. Public trust in AI technology depends on its perceived fairness and lack of bias. Legal and regulatory compliance with evolving AI governance requires vigilance against bias. I believe that the ethical practice of AI is crucial to a company’s reputation and commercial success, reflecting a commitment to global and cultural sensitivity.
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Strengthen explainability. Closely related to ethical use is that AI and everything around it must be explainable, verifiable and defensible. Technology professionals must be able to tell the story of how data is calculated, connected and transformed to those who are asked to approve projects and budgets. Stakeholders will be wary of what they don’t understand and what doesn’t seem transparent, especially in terms of fairness and bias.
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Developing AI talent. What skills do you need to be an AI professional? Yes, deep programming skills and a solid foundation in mathematics are table stakes, but gone are the days when you could throw something at a programmer in the corner who doesn’t interact with people. An AI specialist must possess soft skills and collaboration skills. They will work with legal, finance, marketing and human resources and will be expected to communicate effectively and directly.
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Integrate AI throughout the business responsibly. AI is a strategic business capability that can and should impact all parts of an organization and will drive collaboration like you’ve never seen. It is therefore necessary to have a business strategy for its use, evaluate the preparedness of staff, processes and platforms and put in place a framework for its responsible use. This is a critical component of understanding and managing risk tolerance, being compliant, and most importantly, building trust in AI technologies.
Once the excitement of last year dies down, the transformative potential of AI is within reach in 2024, if we can put these five priorities into practice. We go to work.