IBM's Anshul Sheopuri on curiosity, continuous learning & AI

Anshul Sheopuri is the VP & CTO, Data, AI & Offering Strategy, HR and IBM Distinguished Engineer. Anshul is responsible for re-inventing people data and offerings via AI. He is a digital transformation leader with proven ability to drive measurable business outcomes by driving changes to process, platforms, products and people. His work resulted in $100M benefit to IBM in 2018 alone.

Previously, Anshul was Senior Manager, Digital Research, at the IBM T J Watson Research Center, where he led a team of researchers working on innovative big data digital technologies in areas like real-time bidding algorithms for paid media optimization, spatio-temporal analytics for mobile personalization, and omni-channel content personalization using NLP and machine learning techniques.

Here are the excerpts of the interview with Anshul.

You lead a team of data scientists, people analytics practitioners, and engineers who use data to transform the employee experience. How do you bring value to the business?

The people analytics journey has mirrored the evolution of our HR function, moving from process to experience. A decade ago, the analytics team focused on reporting operational metrics like the cost to hire. Now, we're focused on delivering insights that solve valuable business problems and compelling user pain points. We've incorporated a number of AI tools to help with better decision support, better employee experiences and productivity. Our journey from operational reporting to AI has transformed the way our users experience our offerings - for example, our employees experience learning via a contemporary digital platform that has a Netflix-like experience and delivers AI-based personalized recommendations. 

How do you see the evolution of HR and talent from a technology perspective?

As HR functions evolve from ones focused on process to experience and outcomes, this has required us to transform:  

• Contemporary digital platforms with open architectures enabling rapid development
• Products that are co-created with users, and solve compelling business problems using AI-infused insights
• New skills on teams that are emerging, from offering management to architects
• New ways of working - agile iterations with a focus on low-fidelity prototypes and agile iterations, so we can learn from the users and incorporate their feedback in sprints

How are next-gen technologies such as AI going to change jobs? How can employees adapt to the new and ever-changing environment?

There’s no doubt that AI will change 100 percent of jobs across all industries. In fact, in the next three years, more than 120 million jobs in the world’s 10 largest economies will need retraining or reskilling. Continuous learning is necessary for employees to not only adapt to this new and ever-changing environment but shape it as well. It’s about employees having the propensity to learn and companies to help ready their employees for skills of the future. At IBM, we invest between $400 and $500 million annually on training, including AI skills investment to make sure our employees understand how to create and apply AI technologies. Last year, we launched the AI Skills Academy for our employees to help them understand how to interact with AI technologies and how it impacts their career and the company. Our employees also participate in our digital badge program, where we’ve issued closet to 1.5 million badges since 2016. 

What's your take on top skills that will define the future of work?

In the digital era, skills have become the most critical issue of our time. Given the half-life of skills is shrinking, curiosity and continuous learning are more important than ever. 

What's your advice to HR leaders who want to leverage people analytics and AI? 

It's important to resist the temptation to adopt shiny objects without having a clear roadmap and prioritized projects focused on business outcomes.  Here’s what we learned from our own experience at IBM: Adopting a digital architecture foundation with cloud and robotic process automation first –or even in parallel - can provide cost savings to reinvest for future digital initiatives and ensures you can continue scaling the work.

With half the activities which people are paid to do globally could theoretically be automated, what impact will automation have on work according to you?

The real potential is in AI’s ability to work in partnership with people. Embracing automation and process efficiency like virtual assistants have allowed employees to work more effectively and move to higher value work. As we think about automation, it's not just about lifting and shifting. It's about redesigning the process. As we transitioned to a cloud-hosted compensation planning solution with automation in payroll processes, we have infused AI in the decision support. This has created a host of new HR jobs, as well as upskilled the team made up of designers and HR practitioners who can train chatbots, digitally savvy comp subject matter experts and AI HR operations.

There’s no doubt that AI will change 100 percent of jobs across all industries. in fact, in the next three years, more than 120 million jobs in the world’s 10 largest economies will need retraining or reskilling

What excites you about the HR tech industry right now, and what's the way forward?

We’re experiencing an explosion of opportunity in the HR technology industry, especially with new roles and profiles emerging. As I meet with students, I see a lot of passion and energy in diverse skills and backgrounds, whether it’s people in traditional HR tracks or even electrical engineers and designers. Just yesterday, I met with a major in psychology and a minor in computer science who was interested in a career in HR.

Our opportunity is in shaping industry thinking in the development and use of AI. It comes down to trusted AI built by diverse teams:

• Who builds the technology: having diverse and inclusive pools of talent is key to how we design and build it. The AI should be designed to be fair, robust and explainable. For example, our AI-powered compensation decision support solution is trained by compensation experts and exemplary managers apart from historical manager decisions.
• How it should be used: the ultimate decision maker is the user who is empowered to make decisions based on evidence provided by the AI, whether it’s selection, learning or pay.
• Continuously learning from user feedback, so the AI is always getting better.