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5 AI Priorities to Stay Competitive

In 2023, we learned just how big an impact AI will have on the world. What happens next?

Jeromey Farmer

February 8, 2024

3 Min Read
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Source: Alexey Kotelnikov via Alamy Stock Photo

COMMENTARY

Artificial intelligence (AI): Since the invention of the operating system, we haven't seen a technology poised to have such far-reaching impact on the way we work and live. And organizations are keen to get in on the action. In fact, according to a recent study by Avanade, in which we surveyed more than 3,000 business and IT executives globally, 92% of respondents agree that their organization needs to shift to an AI-first operating model this year to stay competitive.

But rather than shifts, I see sprints. Many organizations are reacting to the hype, rushing to satisfy board curiosity and deploying AI somewhere (anywhere) to check a box. They're often jumping ahead of the important and tough work of finding the right problem for the technology (be it a new revenue stream, higher profitability, process optimization, or cost savings), understanding their AI readiness, and designing a road map that matches it.

The technology industry at large has some important but tough work ahead, too, ensuring that we're leading by example and designing and applying AI responsibly. After all, just because we can use AI for everything doesn't mean that we should.

Closing the Gap, Mitigating Bias, and More

So, as we all absorb the mania we were exposed to in 2023, I recommend that individuals, organizations, and the overall technology industry focus on these five priorities in 2024.

  1. Closing the gap between AI advancements and government regulations. Although the United States government and the European Union announced policies around the use of AI, we're still living with a Wild West-type framework. Advancements in the application of AI will require access to tons of data, and this will clash with privacy concerns. And yet we must address how to maintain privacy in a way that still allows innovation to happen. I believe there's a huge opportunity for technology firms to do what matters and come forward to invest in privacy-preserving technologies.

  2. Mitigating bias and ensuring ethical use. Mitigating bias in AI is essential for fairness and equality, as biased systems can perpetuate social inequalities. Accurate and reliable outcomes depend on unbiased AI, especially in critical applications like law enforcement and hiring. Public trust in AI technology hinges on its perceived fairness and lack of bias. Legal and regulatory compliance as AI governance evolves mandates vigilance against bias. I believe that ethical AI practice is crucial for a company's reputation and commercial success, reflecting a commitment to global and cultural sensitivity.

  3. Strengthening explainability. Closely tied to ethical use is that AI and everything surrounding it must be explainable, auditable, and defensible. Technology professionals must be able to tell the story of how the data is calculated, linked, and transformed to those who are asked to sign off on projects and budgets. Stakeholders will be wary of what they don't understand and what doesn't seem transparent, especially around fairness and bias.

  4. Developing AI talent. What expertise do you need to be a practitioner of AI? Yes, deep programming skills and a solid foundation in mathematics are table stakes, but gone are the days when you can throw something to a programmer in the corner who doesn't interact with people. An AI specialist needs to possess soft skills and collaborative capabilities. They'll be working with legal, finance, marketing, and human resources, and they must communicate in an effective and straightforward way.

  5. Embedding AI across the business responsibly. AI is a strategic business capability that can and should impact all parts of an organization, and it's going to foster collaboration like you've never seen. You must therefore have a business strategy for its use, assess the readiness of your people, processes, and platforms, and put a framework in place for its responsible use. This is a critical component of understanding and managing risk tolerance, being compliant, and most importantly, building confidence and trust in AI technologies.

As the hype of last year settles, AI's transformative potential is there for the taking in 2024, if we can get these five priorities right. Let's get to work.

About the Author(s)

Jeromey Farmer

North America Head of Data & AI Advisory, Avanade

Jeromey Farmer has over 20 years of experience in data science, product innovation, cloud, digital strategy, advanced analytics, research and critical analytical intelligence supporting senior management to drive development and execution of key strategic initiatives and business decisions. He is a proven academic leader in developing, launching, and growing academic programs in the data and technology space. Jeromey is dedicated to formulating and solving complex business problems to meet business and customer needs creating a sustainable model for success.

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