Artificial intelligence (AI) projects regularly fail in business, not because of technical limitations, but because leaders fail to clearly define what AI is, where and how it can bring the most added value to their organization.
CIOs have the opportunity to exert powerful leadership by asking six questions, opening up as many discussions with their company’s leaders to fill this gap.
1. “What does AI mean in our business?” »
First, make sure everyone shares a common understanding and language of what AI is in the context of their business. Bring it all down to simple use cases and examples. Talk about three categories of AI: systems that behave like humans (or whose human-machine interface tries to imitate it), such as chatbots; systems that automate human tasks; and systems that generate higher level information.
2. “How do we get AI to cooperate with our people to get results?” »
Discuss how AI will interact with your employees: does it replace them, help them work better, or work alongside them? The three methods are equal, but the expected value and the risks to be anticipated are different for each of the approaches. Get executives used to categorizing AI opportunities this way.
3. “Is AI transparent? »
Determine how much you need to understand how the AI does its job. Companies must avoid unnecessary, unintended, or even dangerous or illegal biases in algorithms. Imagine a clever marketing algorithm that accidentally turns out to discriminate based on race or gender. The need for transparency can lead us to choose one AI technique over another, even if it is less efficient. Managers must develop a keen awareness of this question of the explainability of algorithms.
4. “What AI-powered business opportunities should we seize?” »
Based on the answers to the three questions above, leaders must decide whether to apply artificial intelligence to certain business lines. These choices can be based on the three-part typology of AI mentioned in the first question, mapped to the different areas of the internal supply chain and the ecosystem. This helps ensure that you are not AI “fashion victims”, but instead consider the most valuable opportunities across your business.
5. “How ready are we to rely on AI?” »
By combining the results of questions two and three above, leaders can make high-level decisions and command policies about how much AI automation is desirable and how transparent AI should be. in different parts of the business. For example, a company may be comfortable with a fully automated “black box” that flags potential fraudulent transactions, but the systems involved in hiring decisions must include the decision of humans “in the loop” and demonstrate of transparency.
6. “How are we going to manage and mitigate AI risks?” »
Even if one makes wise decisions about how to deploy algorithms, the residual risk does not go away. Never. The sixth conversation should focus on the types of risks, how to mitigate them, and defining stakeholder responsibilities.
These hazards can be serious injury or death with critical systems like self-driving cars. For most organizations, these risks affect their financial health, their reputation or their internal operations. Developing a portfolio of techniques such as insurance coverage and creating radical transparency with all stakeholders is essential.
Dave Aron is vice president of research and an analyst at Gartner. He specializes in analyzing the strategies of management and CIOs, in their approach to technologies and their key activities. This specialist has a career spanning more than twenty years and has crossed paths with several hundred organizations.
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Gartner: Six Key CIO-Executive Conversations to Drive AI Success
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