Generalists have long been regarded as useful all-rounders, but rarely as a decisive strategic force. While specialists were perceived as “true experts” in many companies, generalists eked out an existence away from the limelight and, at best, in the second row. However, as already became clear in the first two parts of this series, the focus is shifting.
Generalists can recognize complex interrelationships and contribute strategic foresight. This becomes a decisive factor in a company’s success when they have creative freedom and are not reduced to operational tasks. At the same time, generalists are key bridge builders who break down silos, promote innovation, and contribute measurably to value creation through networked thinking. Studies show that their way of working accelerates market launches, improves decision-making, and makes companies more resilient.
And now, a technological leap is causing another and perhaps final turning point: artificial intelligence. More specifically, AI is changing the rules of the game so profoundly that the strengths of generalists are becoming more visible and valuable than ever before.
The new starting point: AI shifts the bottleneck
Generative AI (Gemini, ChatGPT, etc.) automates tasks that were previously considered specialized expertise on a large scale. Research, evaluation, texts, designs, some programming, initial data analysis—tasks that used to be reserved for specialized teams can now be completed in minutes. The output becomes faster, more comparable, and more standardized (if AI is used professionally). This creates a new bottleneck logic: it is no longer execution that counts, but classification. Not creation, but prioritization.
In the past: Value creation through specialist knowledge.
Today: Value creation through context and connections.
This is precisely where generalists come into their own!
Of course, the respective output must be checked for authenticity and consistency. Even generalists cannot afford to place blind trust in AI.
Why AI increases the value of generalists
AI provides generalists—regardless of their position—with a small private team of specialists. This is why the symbolic image of a multi-armed employee comes quite close to reality.
1. Relief from routines
AI takes over repetitive work—summaries, documentation, preparation, data research, initial drafts. Generalists gain time for coordination, decision-making, and strategic navigation. They move closer to the core questions: What is relevant? What is feasible? What is right? Or, to put it another way: They have time to “think” and thus to plan, steer, and act.
2. Scalable support instead of bottleneck knowledge
AI provides expertise on demand. This democratizes specialist knowledge and lowers the barriers to entry into new domains. Generalists benefit from this effect more than specialists because they are already accustomed to diving into the unknown and working at the intersection of different fields. AI reinforces this breadth.
3. Better basis for decision-making
Dashboards update automatically (if interfaces are available), analyses are generated in minutes, and scenarios can be simulated. Generalists who prepare decisions gain depth and speed. Classification and prioritization increase in value.
4. Interdisciplinary pattern recognition
AI reveals connections—but does not evaluate them. Generalists recognize patterns across silos, connect technology, business, and organization, and classify AI outputs in terms of reality and quality.
5. Generalists benefit more than specialists
While AI automates narrowly defined specialized tasks, the “connecting” tasks remain human. The combination of overview, context, communication, prioritization, and, in some cases, leadership becomes a bottleneck factor.
AI is eating away at routine specialization—and strengthening those who orchestrate the big picture.
Generalists as translators between people, machines, and organizations
AI provides opportunities. But it does not set priorities. This is precisely where new roles arise that generalists are perfectly suited to fill.
Organizations need people who:
- Assess technical potential,
- Classify opportunities and risks,
- Translate requirements,
- Orchestrate processes,
- Bring stakeholders together,
- Maintain an overview (big picture),
- Create and/or follow visions and strategies.
Generalists act as translators between technology, strategy, and operational implementation. They connect what AI generates with what the organization needs, thereby separating the wheat from the chaff. AI does not make this translation and transfer work any less important—it makes it central.
This is particularly true because many managers underestimate their teams’ actual use of AI. Studies show that employees are already using AI much more intensively than assumed. Companies will be stuck in transition in 2025/2026: AI will be used without understanding the strategic consequences and recognizing the strategic potential. The need for roles with assessment, orchestration, and prioritization skills is growing every day.
Not to mention the legal assessment of AI shadow software.
AI as an amplifier of the generalist role
1. Better communication
AI supports structure, clarity, and speed in communication. Generalists benefit because they bundle complex topics and make them understandable. AI does the groundwork—generalists contribute context, relevance, and tone.
2. Faster learning curves
Generalists (sometimes referred to as scanner personalities) learn quickly anyway. AI exponentially increases their learning ability. Tools fill knowledge gaps, explain technical topics, provide examples, and simulate scenarios. This expands their connectivity to new domains.
3. Greater impact in interface roles
Whether in marketing and sales, product and management, or IT and specialist departments, AI is changing the way we work together. Generalists shape these interfaces because they oversee processes and connect teams.
The more AI is used, the more important this coordinating role becomes.
4. Focus on prioritization and problem definition
AI supports solution finding. However, the quality of the output depends on how the problem is formulated. Generalists define problems, structure decision-making spaces, and prioritize measures across departmental boundaries—thereby increasing the effectiveness of AI in the company.
Risks and misunderstandings
The revaluation of generalists does not mean that everything will automatically improve. Four common misconceptions:
- AI does not replace responsibility.
Outputs are automated, decisions and (strategic) classifications are not. - Generalism is not arbitrariness.
Right now, it is becoming clear that breadth without depth, without systematic thinking, and without strong communication skills is losing relevance.
(See also the theory from Part 1: The opposite of a specialist is not a generalist. A generalist is a “specialist in general knowledge.” You don’t automatically become a generalist if you are not a specialist.) - Bad processes remain bad processes.
KI beschleunigt. Sie beschleunigt aber auch Chaos, wenn Strukturen fehlen. - AI is becoming more professional.
Simply “playing” with AI is not sufficient. Its use is highly professional and purposeful. AI is more than just having ChatGPT create emails.
What’s more, the lack of AI expertise at management level is a real risk. Many companies do not have a clear strategy for AI – or are too slow to implement it.
Generalists can fill this gap, but only if they themselves have invested in basic AI logic.
The use of AI must not be an end in itself, as the saying goes, but must be embedded in the strategic framework of the company.
A “Bat-Signal” for all generalists.
The new role mix: hybrid generalists
AI does not turn generalists into specialists—but it does turn them into hybrid roles.
Broad-minded, technologically competent, networking and coordinating—and thus, to a certain extent, also “facilitating.”.
New roles are emerging across organizations:
- AI orchestrator
Connects departments, data, AI tools, and business logic. - Prompt strategist and validator
Design prompts, review AI outputs, connect them to company knowledge. - AI-augmented Project Manager
Use AI for planning, risk analysis, and decision preparation. - Change & Adoption Manager
Supports AI implementation, trains teams, measures ROI, and optimizes workflows. - Hybrid Domain Integrator (π-shaped)
Combines several sub-disciplines – e.g., marketing, data, and AI. - Ethics & Impact Coordinator
Assesses risks, manages compliance, and ensures responsible AI use.
Generalists become architects of workflows and value chains – not executors.
As described in Part 2, generalists are therefore much more integrated into a company’s revenue generation, which makes their position and role crucial for the economic future of a company.
Practical examples: Where generalists immediately benefit from AI
1. project preparation
AI assists in scanning large amounts of information. Generalists structure goals, risks, stakeholders, and measures—and create clear decision-making frameworks.
2. Funnel analyses
AI analyzes segments, patterns, and hypotheses. Generalists interpret, prioritize, and translate outcomes into strategic and operational steps.
3. leadership preparation
AI generates briefings, decision-making bases, and stakeholder analyses. Generalists moderate discussions, weigh options, and provide guidance. Or they take on the leadership role themselves, with or without a title.
4. Change processes
Stakeholder mapping, scenarios, rollout planning—all supported by AI. Generalists orchestrate implementation, moderate resistance, and define guidelines.
5. Customer dialogue
AI generates initial analyses. Generalists define the problem, assess the situation, and derive concrete options for action.
This shows that AI enhances the impact of good generalists because it shapes orientation from data and turns possibilities into decisions.
Conclusion: AI speeds up work—but not understanding
AI increases the speed of execution. But understanding and connecting the dots remains a human task.
Generalists contribute the overview, contextual competence, and systemic thinking that AI cannot replace. They connect technology, people, and organizations. They orchestrate rather than execute.
And it is precisely this ability that is becoming a key resource in companies that want to use AI seriously, strategically, and profitably.
The organization of the future does not need silos, but people who create connections.
AI does not make generalists obsolete—it makes them visible. And more effective.
For many companies, this will be the decisive productivity lever in the coming years.
Plot twist: Will specialists now become unemployed?
Artificial intelligence (AI) has the potential to take over certain tasks from specialists, especially those that require less in-depth expertise. Nevertheless, there will always be activities that require a high degree of expertise and in-depth knowledge, which is why true specialists will remain indispensable. At the same time, AI enables generalists to efficiently handle the initial stages of specialized tasks, allowing specialists to focus more on complex and demanding areas—which, among other things, require even deeper specialist knowledge. It should be noted that AI could replace less qualified or inexperienced (junior) specialists in some cases, which could have long-term implications for the labor and training market. This social dimension deserves separate consideration.
