How your AI-enabled enterprise is underusing your people – and what to do about it

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RapidMiner – Business Reporter Client

Business Reporter: How your AI business isn’t using your people – and what to do about it
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Three out of four CEOs are afraid to leave the business in the next five years if they don’t scale artificial intelligence (AI). Why? Because of the revolutionary impact of AI on businesses. AI can not only help increase revenue, reduce costs, and better manage risk, it can also improve day-to-day processes and operations to turn your organization into a productivity machine.

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Many businesses are already using AI, but what they often don’t realize is that they could do even more by using the secret weapon they already have: their people. We covered this topic in depth in a recent video interview with Peter Lee, President and CEO of RapidMiner, and Andy Walter, Board of Directors and Strategic Advisor at RapidMiner and former Senior Vice President of P&G.

How businesses underutilize their people

Most companies do not prioritize data literacy for everyone, meaning that data skills are only expected from data experts. However, businesses have a wealth of experience across the organization, from IT to marketing to warehouse workers, who all know their area of ​​business like the back of their hand. Currently, organizations are not associating this invaluable business context with data expertise, which is a huge missed opportunity.

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In addition, disparate business functions leave little room for effective use of analytics—there is no easy way to collaborate. These disparate structures are used by organizations that choose to either outsource their data science projects to costly consultants or hire additional individual data scientists internally. Both of these approaches are short-term solutions at best and waste so much in-house talent.

Three strategies for leveraging your people and data

Pump up your talent

Analytics is a team sport, and existing employees (for example, subject matter experts in various business units) already understand the business context of the problem that data science initiatives are trying to solve. Team members who don’t necessarily have the word “data” in their title can benefit from learning how to apply data science to their day-to-day work, while data science experts will benefit from understanding the broader business context, which they are working on.

Executive sponsorship is vital to encourage and create the basis for ongoing collaboration. Upgrading existing employees will not only eliminate the need to hire new talent in a highly competitive marketplace, but will also make existing employees feel more valued and respected. According to interview according to Tableau and Forrester Research, 80% of employees are more likely to stay at companies that provide them with the data skills they need.

Demonstrate the value of AI

Some employees may be skeptical at first about how AI will impact their work and therefore what their participation in AI initiatives will look like. Demonstrating the value of AI to employees across the organization shows them how AI can add value to their own work, resulting in greater enthusiasm and engagement.

Employees can gain hands-on experience with AI, achieve real results, and begin to integrate AI into the culture of the organization. This will lead to greater familiarity with data science, greater data literacy and, of course, more valuable results.

Implement the right tools

The final ingredient for organizations to maximize the potential of AI is having the right tools and resources. A multi-user data science platform like RapidMiner enables multi-skilled workers to complete data science projects and independently create real business value powered by artificial intelligence.

Thanks to the multi-user tool, anyone in the organization, regardless of experience, can use AI to automate processes, create new applications and predictive models. Platforms like RapidMiner provide organizations with a central hub for collaboration and communication on all ongoing data science projects, bringing previously disparate team members closer together.

The message to organizations is clear: Now is the time to use your own talent to fulfill the promise of AI. By teaching your employees new skills, showing them the positive impact of data science on their day-to-day work, and giving them the tools they need to succeed, you will not only break down destructive organizational silos, but also create a data-driven workplace culture. According to Miro Kazakoff, senior lecturer at MIT’s Sloan School of Management, “In a world of more data, companies with more data-savvy people win.”

Learn more about the critical aspects of creating a successful artificial intelligence corporate strategy. Or learn more about RapidMiner’s fully transparent all-in-one solution. data science platform for the enterprise.

Originally posted on business reporter

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