Artificial Intelligence (AI): 8 habits of successful teams

Artificial Intelligence (AI): 8 habits of successful teams

What are teams succeeding with artificial intelligence doing that you can emulate? Take a look at these best practices and strategies for AI work

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5. Focus on proof of value rather than proof of concept

How much will  the AI solution help the organization save or earn?

Before implementing AI, successful AI teams work with business stakeholders to get clear about what KPIs the AI-enabled solution will impact, what problems it will solve, and how much it will help the organization save or earn, Simion says.

Smart AI teams validate any quantifiable outcomes with a trusted financial executive or function, Earley says. “Including the right people who can ride along and help quantify the benefits (or believe the ROI calculations) will ensure that the business impact measures are taken seriously,” he says. “The risk is that the benefits will not be achieved but it is better to know that sooner than later.”

For those projects where the work is more foundational (with no direct ROI), the focus should be on verifying the link between the initial investment and the eventual ROI-generating applications that will result, Early adds.

6. Secure executive sponsorship

Active participation from an executive sponsor who has credibility and influence in the organization is critical for strategic AI initiatives. “The message to the enterprise will be that the project is not that important if sponsors are not involved and holding people accountable for results,” Earley explains.

The key to getting high-level support is demonstrating its positive business impact. “The more thorough the plan (with risk mitigation), the greater the likelihood of getting a strong sponsor who will risk their political capital for such a project,” Earley says. “I have seen sponsors turn down funded projects because they did not want to take on the risk of failure even though many stakeholders wanted to move forward.”

7. Prioritize pragmatism

AI has tremendous transformational potential, but those who succeed with it focus on realistic, practical use cases that make sense based on where their organization is on its AI journey. “To ensure your AI-enabled solution has a successful deployment, particularly in the current business climate, where many are facing budget constraints, it’s important to earn executive buy-in from key stakeholders within the company,” Simion says.

“There may be ongoing initiatives to build and expand from, or new projects that are logical and reasonable to complete. By showcasing the business outcomes that can be achieved in real-time with a fast-paced deployment, you will not only earn the executive sponsorship you seek but empower the rest of your employees as they witness the benefits.”

8. Focus on user adoption and experience

“The goal is for everyone in the organization to be able to extract insights in real-time,” Simion says, “so it’s important to find ways to make the solution easy to use and available.” Successful AI teams invest in change management specialists and processes. “Much of AI success lies in getting buy-in and ensuring that users trust the system output. That cannot be assumed,” Earley says. “Socialization, education, and ongoing user engagement are critical.”

[ How can automation free up more staff time for innovation? Get the free eBook: Managing IT with Automation. ] 

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