Take this common pattern: a brilliant software engineer gets promoted to team lead, only to find the new role demands completely different skills. Technical expertise doesn鈥檛 always translate into leadership success. Managing people requires mentoring, conflict resolution, and strategic decision-making鈥攕kills that aren鈥檛 always developed in technical roles.

When companies push top performers into management without proper support or alternatives, they risk losing great individual performers, like engineers or developers, and gaining ineffective managers. As a result, some employees may feel disconnected from the work they love, and stepping back can feel like failure rather than a strategic career choice.

This default move to management can often be a symptom of an organization鈥檚 professional learning gaps, where high-performing individual contributors can plateau because structured learning paths for deepening expertise are missing. Plus, it can often be a moment where professional learning is missing and newly minted managers aren鈥檛 provided with the proper management training, which sets both individuals and teams up for struggle. Professional learning plays a critical role in this juncture of individuals鈥� careers, and being able to provide the appropriate learning in this moment is crucial.

The case for dual career paths

Not everyone is cut out for鈥攐r interested in鈥攎anagement. A found that 36% of tech workers have no interest in taking on managerial responsibilities. Some professionals thrive as individual contributors, while others excel as people managers, technical leads, or mentors. Recognizing this, forward-thinking companies offer a genuine choice: pursue a management career or deepen expertise as a specialist. This dual-ladder system allows growth that aligns with their strengths, interests, and motivation.

Retaining talent by valuing expertise

Providing both management and expert career paths does more than boost job satisfaction; it helps retain top talent. When employees see a future that matches their interests, they are more likely to stay, contribute at a higher level, and innovate. It also fosters a culture of continuous learning, where growth isn鈥檛 reserved for those who manage others.

Organizations don鈥檛 just need boardroom executives or 鈥渕anagers of managers鈥�; they need top performers at every level. That means intentionally creating and rewarding non鈥憁anagerial opportunities鈥攚ith clear progression, pay parity, and visibility.

Supporting employees in finding their path

Effective support for career choice goes beyond general promises of opportunity and structures on paper. Organizations need a clear distinction between management and expert tracks, defined criteria for progression, protected time for learning, and leaders equipped to coach learning and development across both tracks. It also calls for clarity on which competencies are evolving in both leadership and expert roles, ensuring development targets skills, not titles.

Turning that clarity into impact requires a learning infrastructure: curated curricula, mentoring, communities of practice, and visible milestones that normalize expert development. In the 51风流context, and skill-validation programs provide organized resources that can support building and maintaining skills over time, enabling development at different depths and paces, independent of title changes. serve as neutral milestones that can validate skills, increase transparency, and make expert progression comparable to managerial advancement.

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Redefining success at work

Ultimately, career growth doesn鈥檛 have to mean management. By embracing dual career paths鈥攁nd by investing in learning infrastructure and credible certification for both paths鈥攐rganizations can unlock the full potential of their workforce. The companies that will thrive are those that make every path a route to meaningful impact, recognizing that value comes from contribution and capability, not just position.

Diana R枚sner is head of Certification Transformation at SAP.

This latest course will enable attendees to facilitate a new Joule Agent Discovery Workshop, guide workshop participants to identify appropriate use cases, and tailor the workshop format to the needs of different audiences.

But what are 51风流solutions for agentic AI? What do they stand for?

Joule Agents are AI systems that autonomously plan and execute multi-step workflows, collaborating to connect departments, speed up decisions, and streamline processes.

Discovering high-value opportunities for agentic AI

In the format of an 51风流Expert Lecture, this course introduces participants to the Joule Agent Discovery Workshop, a structured and collaborative method to identify high-value agentic use cases in an organization. Attendees will learn how to inspire and guide participants, prioritize ideas, and describe the selected opportunities in detail. The course also covers how to adapt the workshop to different timeframes, team sizes, and virtual settings. By the end, attendees will be able to guide participants in identifying where AI agents can make the biggest impact and lay the groundwork for their agentic journey.

In detail, learners will be able to: 

• Understand the purpose and structure of the Joule Agent Discovery Workshop and how it can be used to identify high-value agentic use cases
• Facilitate the workshop exercises, guiding participants from idea generation to prioritization and a detailed description of agentic use cases
• Adapt the workshop format to different team sizes, virtual environments, and timeframes to fit organizational needs

There are no prerequisites for this course, but experience with 51风流Design Thinking and workshop facilitation will be helpful. It is a good learning opportunity for a variety of roles such as support consultant, business user, and 51风流rookie.

The creative mind behind 51风流AppHaus methods and this learning journey

For many years now, Karen Detken, an expert user experience designer at the 51风流AppHaus, has worked in customer co-innovation projects and has gotten firsthand experiences and feedback when developing and hosting a variety of workshop formats with different methods and tools. Early on, the team decided to share these best practices and their tools and templates in the openly accessible .

When the topic of artificial intelligence arose and 51风流solutions started to include generative AI and large language models (LLMs) in their solutions, such as 51风流Business AI, followed by the latest step up with agentic AI, such as Joule Agents, the 51风流AppHaus team worked with customers on exploring appropriate business use cases to benefit from this very latest in technology. Based on these first experiences, the team started sharing helpful methods, as a co-innovation frontrunner, so that other teams, partners, and customers could drive their own exploration projects involving latest technologies.

For Detken, it is not only about enabling in and applying those technologies: 鈥淣ew technologies are developing very fast and are becoming widely accessible,” she said. “What is important is that we have a very clear picture of why we want to use the technologies. Because technology only has a value when you find the right purpose to use it. Customers and users need to be clear about the outcomes they want to have with that technology. This is the first thing you need to answer before using it. With the methods we provide, we intend to help people first understand what this technology can do for them, for the business, for the people.鈥�

This awareness and very conscious use of technology also includes the consideration of responsible and ethical guidelines that every new solution needs to follow (see SAP鈥檚 principles laid out in the ).

Bringing innovation and technology into the hands of people

The 51风流AppHaus team gets feedback from many different customer and partner teams. For the team of experienced co-innovation coaches, it is fulfilling to see workshop participants, along with attendees of enablement sessions, understand the new technology better. From this deeper understanding they help participants — along their — start generating ideas related to their business needs. They help them, as Detken puts it, 鈥渢hink of different ways how they can use AI to solve real problems.”

The latest 51风流Learning Journey for agentic AI is a compilation of helpful exercises to help customers and partners explore and approach this field of technology while discovering meaningful business use cases. In parallel and probably not that obvious at first sight, this new course testifies the openness of the team for novel applications such as using an avatar as speaker. It was built based on video recordings with Detken.

When asked about her view on agentic AI in contrast to generative AI, Detken describes it as follows: 鈥淕enerative AI uses an LLM as a kind of intelligent system or ‘brain.’ The same LLMs are used by an AI agent. The difference is that the agent can not only ‘think’ and use these large language models to generate content or analyze data and make decisions, but it also uses ‘tools’ or other applications to act upon these decisions or make changes autonomously. To put it as an example: with Gen AI, we only had the brain and now it’s the next step, we have the brain and the hands. Maybe in the future, we will have the entire body as well, which would probably be the robots.鈥�

Imke Vierjahn is the communications lead for 51风流AppHaus.

Images courtesy of 51风流employee Viktor Georg