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The Future Of Business: How Artificial Intelligence Can Drive Organizational Change

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OVERVIEW

After years of promise, more and more businesses are realizing the benefits of artificial intelligence (AI) and machine learning. A 2018 survey showed that 47 percent of companies have integrated at least one AI capability into their business process – up from 20 percent in 2017 – and 71 percent plan to increase their AI investments in the coming years.

Change is coming, but that doesn’t mean a rise of the machines. Yes, it will mean job changes for some employees: 120 million workers in the world’s 12 largest economies may have to be retrained over the next three years (2019–2021), but AI won’t replace humans. Instead, industry experts say, AI can help humans make more efficient and transparent decisions.

“AI can do what traditional analysis, scoring or even human capabilities can do, but 10 or 100 times faster, more efficiently and with lower error rates,” says Richard Justenhoven, product development director at Aon’s Assessment Solutions.

AI is not a miraculous solution, however. It works best as a collaborative function across organizations, using trustworthy data and processes to complement a clearly defined business strategy that aligns with organizational culture and values.

“Everything should start with the business priority,” says Preeti Asthana, director and head of Global Programs – Innovations & Partnerships at Aon. “Organizations will differentiate by aligning strategic priorities with emerging technologies to drive innovation at scale.”


IN DEPTH

The ability to collect and process data is advancing rapidly, offering new opportunities to reshape the way businesses operate. Applying AI, organizations can find patterns and draw insights from data to make better decisions.

Businesses are already using AI in customer relationship management, underwriting, fraud detection or security intrusions, automating processes and even social media monitoring to gauge brand perception. AI is also a quickly growing application in talent development and managing human risk.

You’re Hired: AI’s Potential In Selection And Talent Development

AI can help transform the process of identifying and developing necessary talent. Using data generated by detailed questionnaires, AI can help companies pinpoint external prospects – whether or not those individuals have applied for a role. It can also identify current employees who would be suitable for new roles.

For example, an AI-enhanced approach can help a transportation company identify candidates who are most likely to drive safely and in a fuel-efficient way. Or it can improve a business’s chances of finding employees least likely to pose a cyber risk.

“We’re looking to identify core behaviors that might lead to a higher risk profile,” says John McLaughlin, commercial director at Aon’s Assessment Solutions. “Using models that assess the likelihood to engage in certain behaviors, we can offer insights on candidates that help recruiters make hiring decisions aligned with their company’s needs and values.”

And as organizations transform, personality assessment questionnaires can help them identify which existing workers might be suited for new roles in the changing organization, adds McLaughlin.

An organization seeking to fill cyber security roles, for example, might already have employees who possess the right characteristics to fill those positions. Internal hires can be more efficient and cost-effective than sourcing external candidates.

“We can identify what drives performance within these various roles, and then assess whether an organization has talent that can be trained or grown into certain roles,” McLaughlin says. “The data can help identify which people are most able to change, which people can learn faster and better, which are more curious, which are more agile or resilient.”

This internal-first approach can be a resourcing game changer.

“Often organizations aren’t thinking through a growth strategy for innovation based on growing their own internal talent,” McLaughlin says. “The opportunity to apply this type of data in this way can be critical to an organization that is undergoing this type of change.”

Often organizations aren’t thinking through a growth strategy for innovation based on growing their own internal talent. The opportunity to apply this type of data in this way can be critical to an organization that is undergoing this type of change.”
—John McLaughlin, commercial director at Aon’s Assessment Solutions
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AI Adoption: Digital Transformation And Preventing The Data ‘Garbage In, Garbage Out’ Syndrome

To make AI work most effectively for an organization, it cannot be a sole function of the IT department. Instead, AI adoption must be done in partnership between IT and the entire business in order to apply it in a way that provides real benefits.

“AI adoptions are successful when they’re started jointly with the business, rather than saying, ‘This small group from the technology team is going to do it,’” says Rajeev Khanna, chief technology officer at Aon. “Implementing new tools at scale has to be a joint partnership with a sponsor from the business. Successful AI implementation has the right level of push and pull on both sides.”

Taking it even further, Asthana says the most successful AI adopters embark on a full digital transformation. “The most effective adoption outcome requires a transition to a digitally enabled business model that adjusts to an organization’s unique needs,” Asthana says. “That’s when companies unlock AI’s true potential: it can revolutionize how they conduct their business.”

The most effective adoption outcome requires a transition to a digitally enabled business model that adjusts to an organization’s unique needs. That’s when companies unlock AI’s true potential: it can revolutionize how they conduct their business.”
—Preeti Asthana, director and head of Global Programs – Innovations & Partnerships at Aon
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Along the path to AI adoption, it’s important to remind stakeholders and end users that AI applications are only as good as the data – and algorithms – behind them.

“You cannot expect AI to solve problems that you haven’t identified,” says Justenhoven. “For the best results, you’ll have concrete questions or a process that you want to optimize and a desired outcome you want to achieve.” Understanding this at the onset is critical to providing the right data sets that allow leaders to answer these questions.

You cannot expect AI to solve problems that you haven’t identified. For the best results, you’ll have concrete questions or a process that you want to optimize and a desired outcome you want to achieve.”
—Richard Justenhoven, product development director at Aon’s Assessment Solutions
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AI’s Growing Role Will Aid, Not Replace, Human Decision-Making

As technology continues advancing, the ability to apply AI to various aspects of the organization will advance with it.

“There are going to be disruptions in business models and the creation of new ones,” Khanna says. “Things that can’t be done today will be possible in the future. You’ll have a much broader spectrum of communication that’s available at much higher speeds, allowing you to better analyze more information, make decisions and take action.”

While AI can be a significant part of business strategy, human resource decisions or performance management, it’s important to maintain the human element.

“You’re not giving over the entire decision-making process to a machine,” says Justenhoven. “AI isn’t taking the human out of the process.” Indeed, it is more about using these algorithms to provide transparency and enable smarter decision-making.