How Many Employee Experience Copilots should an Enterprise have?

This is a question that I get all the time and thought I would share a perspective based on client-interactions and market analysis.

In the first six months of 2024, we have seen the democratization of AI led by AI players launching and developing new large language models (LLMs) to enable the enterprise market with customizable models.

With AI evolving quickly, copilots are becoming the new user interface (UI) but also an entity to work alongside with. Recently, we have seen several AI copilots launch to market to enable sales, customer service, legal, marketing and of course human capital to create consumer-grade experiences and amplify intelligence to make inform talent decisions.

Copilots are not just a technology capability, it requires a support system including a new operating model, governance to regulate the interaction between workforce and AI agents, built a robust data foundation, and plan for the impact on workforce and skills.

Productivity is just the beginning and as copilots becomes smarter, we will find an ecosystem of human-like AI agents who process vast amounts of information and provide answers and advice to human workers.  For example, a quick win is HR service delivery: HR can build customizable copilots to bring predictive intelligence for case management, self-service, manage employee queries, and benefits enrollment.

The real value is in the customization of human capital copilots. A key question for discussion is around BUILD or BUY copilots solutions.  As of now there are multiple copilots that are offering market-led knowledge, making recommendations and providing talent and organization insights. However, building your own copilots will require to start off with a business case to identify the ROI, align on the prioritized use case (s), do the internal work to prepare talent data and standardize processes. Keep in mind that moving from strategy to execution also brings challenges around leadership, culture, employees’ concerns and enterprise adoption.

4 categories where employee experience copilots can assist the workforce:

✅Recommendations– learning pathways, mobility, analytics etc.

✅Surface Information – copilots to provide enterprise knowledge.

✅Content Creation – prepare materials, presentations etc.

✅Digital Workers– working side by side with HR professionals.

💡How is HR Tech ecosystem responding?

The HR Tech ecosystems is starting to incorporate Gen AI copilots in prioritized use cases across the talent value chain, with copilots with focus on people and skills insights, sourcing, pre-screening and recommending candidates, inferring skills, surfacing enterprise knowledge, accelerating service delivery, suggesting roles and careers paths, as well as providing learning recommendations, AI tutors and creating learning content. 

We are still in early stages and Gen AI will continue evolving changing the HR tech landscape with next-generation copilots, decreasing cost, increasing service-levels, and orchestrating and interconnecting human capital use cases with customer service, sales and operations.

🚨Final Thoughts

The number of copilots will depend on several factors: AI strategy, use case, complexity, resources, and ROI. Below have four key considerations as you start your copilot journey:

1. Experiment, test and learn.
2. Implement AI ethically and responsibly
3. Talent-ready’ data requires a robust data foundation, data governance, and standards.
4. Build AI trust to enable the organization.

The one pager below provides a high-level view including some vendors offering copilots solutions.

I’d love to hear your thoughts! Share your perspective.

Note: All views expressed in this article do not represent the opinions of any entity whatsoever with which I have been, am now, or will be affiliated. My opinions are my own.