A personalized AI goal for every employee at Genesys

TL;DR

Genesys had already put real work into building a skills foundation, and they were the first to recognize that keeping it current was the harder challenge. With TechWolf keeping that foundation fresh and aligned to the market, the talent management team pulled off something most enterprises are still working toward: a personalized, AI-generated goal in front of every employee, each one tuned to their job profile and built on the skills their role will actually need in an AI-shaped workforce.

Business context: an AI company that had to ready its own workforce for AI

Genesys sells AI orchestration to contact centers. When you call a service line, reach the right person quickly, and feel like they understood your question before you finished asking it, there is a good chance Genesys is behind it. The company has been a Magic Quadrant leader in contact center as a service for 11 years running, employs around 7,000 people, and is headquartered in Menlo Park, California.

Selling AI to the market is one thing. Getting your own workforce ready for it is another. Genesys had set building an AI-enabled workforce as a strategic anchor, which raised a direct question from its executives: what AI skills do our people actually have, and how do we know we are making an impact? The talent management team had started its skills work for a different reason. Employee survey feedback kept flagging development and career growth, internal mobility wasn't a priority, and people who wanted new skills or new roles were leaving to find them elsewhere rather than moving across the company. Skills were meant to fix that. AI turned the same foundation into something more urgent.

Challenges: a hand-built skills foundation that could not keep up

Genesys began its skills journey in 2023 the way many companies do, by doing it manually. The team brought in a consultant, put leaders in a room, and worked through the skills and proficiency levels for roughly 700 job profiles. It was tedious, and it was slow.

• The manual approach did not scale. Identifying skills and proficiency levels for 700 job profiles took 18 months. By the time the last profiles were signed off and loaded into Workday, the first ones were already out of date. The honest reaction from the team was that they couldn't trust the data.
• Low trust in the data. There was little confidence that the hand-built job profile skills were the right ones, and no external benchmark to check them against. Leaders could not point to the market and say these are the skills we should be building toward.
• Career Hub only works on accurate profiles. Workday Career Hub uses AI to suggest roles, learning, gigs, and connections, but those suggestions are only as good as the skill profiles underneath them. Employees would go in once or twice, not find what they needed, and stop coming back.
• Executives were asking about AI, and the data could not answer. Leadership wanted to know what AI skills the workforce had and whether the company was closing the gap. Looking at the manual data, the team knew it was not ready to answer that question with any credibility.

How we helped: a living skills foundation, then a goal built on it

Genesys engaged TechWolf in 2025 for two reasons that mapped exactly to its problem: TechWolf could help it understand the skills it already had, and the skills it would need, with both sides aligned to the market and benchmarked against peers. That foundation became the base for everything that followed.

Trusted data. TechWolf's AI Skills Assistant runs inside Workday and infers each person's skills from the work they actually do, then keeps those skills current as roles change. The employee stays in control, deciding what to validate and what to put on their career profile, so the data is both up to date and owned by the person it describes. That solved the staleness problem that manual effort never could.

Executive insights. Genesys had spent about six months rallying its workforce around three shared AI mindset skills: growth mindset, creativity, and critical thinking. Working in a focused sprint, TechWolf took that a level deeper and identified the AI-native skills each job profile actually needs, turning a company-wide message into job-specific detail. The approach was validated enterprise-wide, up to CIO approval, and became the skills backbone for the FY27 AI goal.

Embedded actions. The team then turned insight into something every employee touches. Using TechWolf, Genesys built a personalized AI goal recommendation for every job profile, delivered as an editable goal directly in Workday and woven through the goal-setting, mid-year, end-of-year, survey, and manager processes. Skills stopped being a side project in HR and became part of how people set their year.

Outcomes: from a skills profile to a personal AI commitment

A personalized AI goal for every employee

The headline outcome is the AI goal itself. Every job profile receives a recommended goal anchored on five AI skills: three mindset skills shared across the company, growth mindset, creativity, and critical thinking, plus two AI skills specific to that job profile. The goal arrives as a SMART goal in Workday with a clear note to review it with a manager and make it true to you. It is framed around how AI can support the person's work and what they might do with the time it frees up, deliberately not a warning that their job is at risk.

Genesys iterated on the wording until the tone landed: supportive, specific, and honest about the need to get clearer on what AI means for each role. The team even built in a quiet way to measure real engagement. The recommended goal opens with two placeholder phrases that no real goal would ever start with, so anyone who genuinely edits their goal has to delete them first, which, alongside text analysis, tells the team who actually engaged rather than who merely clicked.

The power of really scaling this to every employee at Genesys is very compelling. We are shifting from I have the skills to now I am using them and thinking about the impact I can make.
— Genesys talent management team, during a TechWolf webinar

A pilot that stuck where the manual effort had not

Genesys launched its skills pilot to 2,000 employees, with most functions represented. The 2,000-person group was assembled in under two weeks, a striking contrast to the 18 months the manual exercise had consumed, partly because by then people wanted the business outcomes and partly out of a fear of missing what other teams were getting. Reception held up: around 80 percent of pilot employees had skills in their career profile, and more than 60 percent engaged with the pilot itself, the kind of adoption the hand-built approach never sustained.

Better development conversations, with less pressure on managers

Because profiles were finally accurate, the conversation could narrow from a long list of skills down to the one or two that matter for a person's current role or their next one. Development discussions that used to wander now had a clear starting point, which took pressure off managers and gave employees a way to surface strengths their manager had not seen, opening the door to a gig or a stretch assignment. Skills became the shared language for growth rather than another form to fill in.

Governance: the employee owns the profile, the data earns the trust

Genesys treated trust as a precondition for adoption, not an afterthought, and built control into the design.

• Human in the loop by default. The Skills Assistant suggests; the employee decides. People have complete control over which inferred skills make it onto their career profile, and the team coached them to be intentional about it rather than accept everything.
• Tone calibrated on purpose. The AI goal went through several iterations specifically so it would support people rather than scare them, and every goal is explicitly editable and meant to be reviewed with a manager.
• Benchmarked against the market. Genesys does not trust its skills just because they are internal. TechWolf aligns the job profile skills to the external market and benchmarks them against peers, which is the confidence the manual, hand-built list never earned and what leaders called a genuinely useful insight.

Project challenges: the honest parts of the journey

• Two manual false starts before the pivot. Genesys tried to build and then maintain its skills and proficiency data by hand, and learned in practice that it could not keep either current. That experience is what made the case for an automated, market-aligned foundation so clear internally.
• Getting the AI goal tone right took several passes. Putting a goal in front of every employee about AI is sensitive. The team rewrote it repeatedly to avoid both alarm and vagueness, landing on language that asks people to get specific about the impact they can drive this year.
• The OKRs evolved as the business did. The program started focused on development and workforce planning. As AI reshaped roles, the goals shifted toward measurable AI impact, and the team treated that change as a feature of the work rather than a failure of the original plan.

Next steps: from pilot to the whole company

The AI goal is now live for every employee at Genesys, with the rollout from the 2,000-person pilot to the full workforce complete. Alongside it, the profile refresh brought the AI skills front and center, cleaned up profiles that had grown long and dated, and added proficiency levels for critical skills.

With goals in place company-wide, the data now feeds the questions the executives started with. Genesys can see where the real gaps sit across the organization, direct learning and experimentation to where they will have the most effect, and bring the same skills foundation into strategic workforce planning. Each employee translates their job-profile goal into a personal AI commitment that fits their tools, their work, and what the year ahead asks of them.