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Is your team’s skill a barrier to AI adoption?

AI
(Image credit: Image Credit: Geralt / Pixabay)

Today’s artificial intelligence can accomplish amazing things, and that’s turning out to be an obstacle. A 2021 survey of 3,500 respondents showed that the biggest problem companies faced with AI is a lack of skilled people made worse by unsuccessful hiring efforts. Almost 20 percent called this skills gap a significant barrier to AI adoption. Companies want (and need) to leverage AI; they just don’t have the people to do so.

The effects of a growing employee skills gap are apparent: Seventy percent of AI initiatives are showing little or no return, according to the University of Pennsylvania Wharton School’s Kartik Hosanagar.

As companies struggle to find the AI talent they need, they also have a hard time reassuring employees that AI adoption won’t lead to widespread layoffs. Workers worry, intensely in some industries, that technology will diminish and ultimately replace their roles. At the same time, however, employees are excited to embrace AI to make their work more productive, efficient, and engaging.

Enterprise AI was seen as optional before the pandemic. Not anymore. Companies must lean on technology like never before to remain relevant and stay competitive. AI will soon become a major differentiator, and every company will be involved with it to some extent — or feel the effects of holding out. As this shift occurs (faster than many expect), it will be vital to understand the impact it’s having on talent, both current employees and potential hires.

AI alone can’t live up to its potential; it will also take people. Now is the time to start thinking about the training and upskilling efforts that everyone will need as artificial intelligence spreads through the enterprise.

The training component of an enterprise AI plan 

Companies face a dual challenge in the coming years. On the one hand, they must deploy robust AI-driven user experiences as quickly as possible to enhance the customer journey and differentiate the company in increasingly crowded markets. On the other hand, they must meaningfully build upon the company’s in-house AI skills through the benefits of upskilling employees, hiring, and partnerships.

The former challenge requires companies to act quickly, while the latter requires being careful and comprehensive. Companies will feel the tension between these challenges as AI becomes ever more ingrained into products, services, and end-to-end operations.

My own company has grappled with this issue. AI has the potential to transform how we serve our clients, but embracing it involved many growing pains as well (as I’ve experienced firsthand). Here are some insights I’ve gained along the way

1. Treat AI like a journey. 

The grand AI experiment is just getting started, but it will never reach an endpoint. Companies will be evolving their AI programs and exploring new applications for years to come. After the first implementation will come the next, along with countless iterations and experiments along the way.

Thinking of AI as an ongoing journey rather than a singular project is an important piece of context, especially for how to upskill staff. A single training session won’t do. More realistically, employees will need regular updates about new AI applications and best practices. It’s important for the C-suite to be involved as well so that they make big-picture business decisions with the capabilities and constraints of AI in mind.

Regular training is also a great way to identify people in your organization with impressive analytics or data capabilities who could be upskilled to serve as AI champions. With the labor supply of AI experts so low and the demand so high, it’s important for companies to look inward to close skills gaps. My company developed an AI center of excellence (COE) to serve as an internal brain trust around all things AI. The COE focuses on prioritized use cases and works across various cloud platforms like AWS, GCP, and Azure (to name a few), plus on a Python-based custom machine learning approach.

Our own AI champions collaborate within the COE, and they’re tasked with evolving our company at the same pace as AI so that we don’t fall behind on this critical issue. Every company should work to develop its own COE to act as a guide along the AI journey.

2. Integrate AI holistically. 

People tend to think of AI as an IT initiative, but it extends across all departments. In fact, marketing, customer service, and sales are the three areas where AI is expected to have the biggest impact. Stakeholders and thought leaders from those departments (and all departments, really) need to be part of the AI adoption effort. Otherwise, this transformative technology could have an underwhelming impact.

Along those lines, AI may be a technology, but it has an impact on every point in the customer experience or the organizational workflow. The point is that IT fits holistically into the organization, so upskilling efforts should reflect that. Everyone should be involved across departments and skill levels. Technical skills shouldn’t be the only focus, either. Upskill your employees to think critically and creatively about AI to uncover new applications and drive growth around innovation.

My company relied on certifications from best-in-class training vendors to help us upskill people quickly but effectively. Certifications apply a focused training methodology to build upon existing skills. This helped us acquire the AI skills we needed to serve our clients but that we couldn’t find easily in the labor market — without putting resources into designing our own training program.

3. Rotate your talent. 

The widening skills gap in AI will only get worse. One way to address skill gaps is by looking internally rather than externally. A hybrid training model pairs the employees with the most AI experience with those just completing training to help make the jump from the classroom to real-life use cases.

It does not see the workforce as a bunch of people in fixed roles. Rather, it sees the workforce as a talent marketplace where the right upskilling efforts can overcome hiring challenges, elevate promising professionals, and bring targeted skills into the company. My company practices a form of the hybrid training model that rotates employees through different roles so they encounter a wide range of problems and solutions. Employees also bring their own expertise and perspective to whatever team or department they rotate into. I’ve seen this approach to enterprise training elevate the skill level across our organization.

It’s important to start upskilling soon. It’s also important to see this as an opportunity as much as an obligation. When your employees have robust AI skills and the technology to match, amazing things are within reach.

Nagendra Bandaru, president Wipro iCORE

Nagendra Bandaru is president of Wipro‘s iCORE global business line, which covers cloud infrastructure, digital operations, risk and enterprise cybersecurity services.