HRTech Interview with Deepika Duggirala, Chief Technology Officer at Alight

Hi Deepika, welcome to HRTech Cube. To start, can you please share a bit about your professional journey and what led you to your role as Chief Technology Officer at Alight?
Before joining Alight, I served as TransUnion’s SVP of Global Technology Platforms. I also spent a significant amount of time at SAP Labs and Motorola Inc. I’ve had the chance to work at some incredible companies, including Yello, SPINS and Nielsen. Each role has been a stepping stone, giving me the experience and perspectives that I now bring to my role at Alight, driving innovation in AI, automation and digital transformation.

Employee engagement is evolving with new models, expectations, and technologies. How do you see AI shaping the future of workforce engagement?
Workforce expectations are no longer transactional but existential. They go beyond pay and benefits. Employees today expect holistic wellbeing that covers physical health, mental health, financial security and more. They expect personalized programs to meet their unique needs.

Employers, for their part, are investing more in benefits. They expect ROI on that spend in the form of increased productivity, recruitment and retention. HR strategies can do this through the smart application of technology, tools, and people.

Personalization is key. Because when it comes to benefits, one size never did fit all. And, perhaps reflecting the huge range of choices we now have when it comes to things like food, entertainment, and material comforts, today’s workers demand benefits that are tailored for their unique needs. Employers now offer benefits that cover things like elder care and parental leave, even pet-related time off.

In fact, fully two-thirds of workers say personalized options across health, finance, stress management, and mental health are valuable to them according to our 2024 Mindset study. They now expect personal, data-driven insights with relevant recommendations that enable them to make the right decisions at the right time.

For today’s workforce, a tech-based experience that spans mobile, desktop, and easy access to live humans is simply table stakes. That’s especially true for younger generations who grew up with the internet at home, iPhones in their pockets, and cloud services everywhere.

Just as data is revolutionizing companies’ relationship with customers, it’s doing the same for HR’s relationship with employees. Data is a secret weapon that helps us serve employees better. Predictive analytics can spot trends like rising healthcare costs or underutilized benefits before they become big problems.

Successful companies are able to turn the expanding range of benefits from a necessary expense to a game-changing differentiator. As a result, the industry is moving towards highly personalized benefits and consolidated employee experience platforms that bring HR, benefits and wellbeing into a single experience.

AI simplifies connections between people, work and life, helping organizations guide employees through important moments. This includes clear communications, decision support tools, benefits guidance, and integrated experiences for candidates, new hires and employees.

Many organizations view AI as purely a tool for automation. How should business leaders think bigger about AI beyond just efficiency gains?
Business leaders should view AI not just as a tool for automation but as a transformative force that can drive innovation, improve customer experiences and create new business opportunities. AI can help in making smarter decisions and fostering a culture of continuous improvement.

Of course, any discussion of technology today quickly turns to generative AI. After a couple of years of excitement, experimentation, and evaluation, many organizations now expect every business function to implement gen AI in some way.

Looking at the HR vertical specifically, HR maybe faces more challenges than other teams when it comes to adopting this game-changing technology. These include concerns around data privacy and security, or biases in training data that can affect hiring or evaluations.

HR must also consider the effect on employee trust and ensure compliance with evolving regulations. These challenges are valid and must be addressed thoughtfully.

Done right, AI promises to improve the benefits experience, making it simpler, more relevant, and more efficient. But the importance of the high-touch human element is crucial to this success and can’t be overlooked. Just one-quarter of employees have access to one-on-one support to help them navigate benefits, whether on the phone or online.

Yet those who do have that support overwhelmingly find it helpful. A simple, intuitive, and fully supported benefits experience changes everything. If we make it seamless for employees to access their benefits, we take them from feeling overwhelmed to feeling in control.

AI promises to transform how we deliver benefits, from personalized plan recommendations to automated support. But while technology is an important enabler, it can never fully replace the guidance, empathy, and high-touch support delivered by trained humans.

AI should enhance, not replace, the human touch. People still need and value real humans to guide them through complex situations. Winning with Wellbeing means the best approach is a blend of smart technology for efficiency and real humans for empathy. That means we can make smarter, more cost-effective choices while still delivering high-quality support that meets employees’ needs. AI in HR can help employers create personalized outreach plans, generates employer insights and automates service delivery functions. For example, if an employee receives a pay raise, a tailored campaign can guide the user toward relevant programs or actions to help them make more informed decisions about increasing their retirement contribution.

What key skills do you believe organizations need to develop to fully leverage AI-driven transformation?
Organizations need to develop skills in data analysis, machine learning and AI ethics. Additionally, fostering a culture of collaboration and continuous learning and experimentation will be crucial to fully leverage AI-driven transformation.

AI is playing a significant role in driving operational agility and workflow efficiency. Can you share specific ways AI is enabling faster and smarter decision-making?
The open enrollment process is often confusing and frustrating for employees, whether they are updating their information from the previous year or completing onboarding as new hires. AI-driven personalized guidance helps employees become better educated and more engaged with their options, ultimately feeling more confident in the choices they make for themselves and their families. With AI-guided enrollment experiences, employees can easily compare plans, simplifying the process.

To simplify and automate the enrollment process, organizations should leverage technology such as provider search tools, plan comparisons, and total plan cost modelers. It’s important to ensure that employees can enroll online and easily access information and resources in one consolidated portal.

Creating an enrollment experience that replicates what users encounter in everyday life is crucial. This includes:

• Real-time updates
• Instantaneous assistance
• Expert insights
• Convenient accessibility

Providing technology, tools, and expert support helps employees optimize their core and voluntary benefits to meet their needs and those of their family members. Delivering targeted, personalized messages after enrollment and throughout the year encourages employees to use benefits wisely and actively engage in programs to improve their wellbeing

How do AI, automation, and digital transformation work together to create long-term business impact?
It begins with data and using that data to help teams deliver business value. Data (and using it correctly) brings completely new insights to a business and provides a real competitive advantage. Data comes from all directions from within and outside the organization – such as business units, operations, customers, supply chain partners and other stakeholder interactions.

The key to future business success is to first capture this continuous flow of business intelligence data.   In a digital business, a foundational data framework can be the equivalent of a satellite navigation system. The more up to date the data, the faster and smoother the journey to the desired destination. All business strategies should have a desired destination and a timescale within which to get there.

Unfortunately, there can be many challenges on the journey to success, and so real-time recalibration is vital. Why? Because even the most sophisticated supercomputers cannot predict the future. They cannot factor in environmental, political and economic discourses that will continue to test the efficiency and profitability of businesses.

In all these instances, as in normal times, data is one of the most valuable assets of any organization. Unlocking its value can be a catalyst to positive business outcomes.

While AI serves its purpose, the true winning combination will be about striking the right balance between people and technology. Organizations that are able to act nimbly and bring their best resources – their people empowered by technology – will be the ones that succeed.

We see this in our own platform, which brings the power of AI together with a high-touch support model.

With rapid advancements in AI, how can organizations foster equity and accessibility in technology adoption?
Organizations can foster equity and accessibility by ensuring that AI technologies are inclusive and accessible to all employees. This involves providing training, addressing biases in AI systems, and creating an environment where everyone can benefit from technological advancements.

What challenges do companies face when integrating AI into their operations, and how can they overcome them?
Companies often face challenges such as data privacy concerns, a lack of skilled personnel, and resistance to change. To overcome these obstacles, organizations should invest in training, adopt robust data governance practices, and foster a culture of innovation.

What’s one personal strategy you rely on to stay ahead in the ever-evolving world of AI and technology?
In technology, as in any other field, it’s crucial to stay curious and keep learning. I stay updated on emerging technologies and developments, including AI, through a blend of continuous learning, hands-on experimentation, and strategic partnerships with others in my field and the business.

I subscribe to various publications, blogs, and podcasts that regularly highlight and review emerging trends, interesting activities, and developments in the startup ecosystem. These sources also provide valuable dialogue and debate on technologies and their applicability. Additionally, I dedicate time to continually learn about the business, including developments in healthcare, insurance, retirement planning, and the benefits administration ecosystem.

I highly value the partnerships and opinions from people in my network. Our product and business leaders possess a wealth of knowledge that I benefit from, as do my peers in technology, whose experiences and feedback on their own learning and experiments are invaluable.

In my personal time, I experiment with emerging technologies that are gaining traction. I also learn a great deal from my teams and the innovation they pursue as they build solutions for Alight. My team is one of my most powerful teachers.

Finally, what advice would you give to business and technology leaders looking to navigate the future of AI-driven transformation?
Companies need to clearly define the outcomes they aim to achieve with AI-driven transformation and continuously measure progress. Once this foundation is in place, various levels of sophistication can be employed to measure and attribute changes in the planned outcomes to the interactions being executed.

We recommend five key considerations for any new AI use case. Thoughtful attention to these factors will ensure a successful launch:

1. Pick the right areas: Focus on problems AI can solve now, not speculative future capabilities. Validate with small, low-risk pilots.
2. Resource wisely: Build in-house for differentiated capabilities and use vendors for commoditized capabilities.
3. Avoid high-risk AI uses: AI will make mistakes; avoid using AI where those mistakes could have severe consequences.
4. Keep humans in the loop: Humans must oversee AI systems. Design AI use cases for human oversight.
5. Measure extensively: Rigorously measure performance, error rates, biases, and business impact. Establish feedback loops.