Three Reasons To Leverage AI And ML To Improve The Employee Experience

Vice President in Cisco‘s Employee Experience (EX) organization, with a mission to reimagine the future of work for employees worldwide.

After a career spent working at the intersection of technology and human experience, I know a couple of things to be true: good artificial intelligence (AI) and machine learning (ML) are incredibly powerful, and the human experience is absolutely mission-critical.

So why don’t we hear more about bolstering employee experience (EX) and human capital intelligence using the power and possibility of AI and ML? When the quality of EX — which, according to Gallup, includes “every interaction that happens along the employee life cycle, plus the experiences that involve an employee’s role, workspace, manager and wellbeing” — declines, the odds are good that your talent engagement and retention isn’t far behind. And as Josh Bersin, global industry analyst and founder of Bersin by Deloitte, said in 2018, “Turnover is so painful with this job market that companies are realizing, ‘I’ve got to take better care of my people or else I can’t grow.’”

AI might be the answer to this challenge. As I’ve recently transitioned from customer experience to EX leadership at Cisco, our group has embarked on a mission to engage our people in a way that’s productive while fostering an intelligent workplace that’s automated, insights-driven and augmented with AI. Here’s why I think the time is now to start leveraging AI to drive an employee experience that connects, empowers and unleashes the potential of your team: 

When you apply AI and ML exclusively to productivity, you miss an important piece of the puzzle. 

AI and ML are great tools that have historically been built around (and applied to support) the idea of productivity for uses like getting better contacts or recommending new products or solutions for the market. And because productivity is such an easy measure, many organizations double down on it. 

But I believe putting 100% of your AI or ML investment in and focus on productivity is a big mistake. Productivity is only one element that supports talent retention and growth. Talent retention is an equation that includes both productivity and employee happiness. As we move into a virtualized world and increasingly do jobs where it’s difficult to measure productivity and output in the same ways, employee happiness may actually become the best indicator of future productivity. When you invest in helping your employees become happier, more purposeful and more engaged, you’re setting them — and your organization as a whole — up to make an impact. 

In many workplaces, EX may be in crisis mode.

The employee experience is in red-alert status for many companies. I don’t hear people today complaining about productivity issues; rather, many people I speak with are grappling with EX challenges like well-being, purpose in their roles and a lack of human connection. An October 2020 Gallup poll found that “51% of workers are ‘not engaged’ — they are psychologically unattached to their work and company.” 

Too often, employees lack clarity on their roles and how they fit into the larger business strategy; thus, they lack an understanding of their career paths. They may be discouraged by a lack of communication and transparency about organizational changes, which can cause trust to erode and engagement to decline.

I believe this is, in part, due to changes in the way we work, particularly as changes begin to take place in light of Covid-19 vaccinations. But these recent developments make it more important than ever for employers to adopt a posture of openness and agility and to identify and embrace the evolving needs of a rapidly changing, diverse and multi-generational workforce.   

AI and ML could offer tangible ways to improve EX. 

You can personalize your AI and ML tools to employees’ roles, organizations and preferences and, at their best, I believe these technologies can help team members work smarter and more productively while fostering their well-being, growth and development.

Here are just a few examples of ways that I envision using AL and ML to foster and measure engagement and happiness in the workplace:

• Leaders could predict burnout based on factors like time spent working and attending virtual meetings. 

• Companies can encourage teamwork and connection by coordinating teammates’ calendars to ensure they are in the office at the same time. 

• Leaders could predict disengagement by analyzing community posts and instant messaging activity. 

• AI and ML can support employees’ social networks with recommendations of co-workers to connect with.   

It’s important to use the power of AI responsibly.

Due to the power and reach of effective AI and ML, it’s crucial for employers to build in governance and guardrails to ensure they use that power responsibly. Virtuous intent and clarity on the use of these technologies are extremely important. A guiding principle we follow within our EX organization is to leverage AI and ML only for the benefit of the individual user — the employee.

There’s no doubt that leaders should tread carefully when it comes to using AI and ML in the EX realm. The application of these technologies within EX should be built around this question: “How can we create delightful experiences and better human connections for our employees?” 

As we move forward with our own AI and ML initiatives, I’m confident that it’s possible to deliver an experience that connects human engagement, purpose and learning for employees’ well-being, growth and development. I see a future in which these technologies will create big breakthroughs in the workplace and unleash an era in which everyone will be able to thrive — employees, customers and the entire business.    

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