The Next Phase of AI Talent Development: How Department-Specific Curricula Offer a Realistic Path to “Organizational Transformation”

The Key to Resolving the “AI-Obsessed Executive” vs. “Lack of Change Agents” Paradox

As highlighted by a Nikkei CrossTech article, there’s a contradiction in Japanese companies: “executives are AI-obsessed” yet “our company lacks change agents.” Isn’t this dilemma a reality for many leaders? While there is enthusiasm for the potential of generative AI, the “execution teams” needed to permeate its use on the frontlines and link it to business results are not being developed. A potential answer to this structural challenge emerges from two recent trends.

The first is the launch of the generative AI learning platform “Comix Academy” by Comix Co., Ltd. Its key feature is a curriculum optimized by department, with over 1,100 courses—the largest scale in Japan. The second is a finding from MMR Research: for SaaS companies hiring sales staff in 2026, “analytical skills” and “generative AI utilization” rank among the top required skills.

These are not just stories about “training services” or “hiring trends.” They are clear signals that “strategic development of AI talent,” which will determine future corporate competitiveness, is undergoing a paradigm shift from “uniform training” to “injecting role-specific, department-specific practical skills.” This article explores the essence of this shift and the concrete actions companies should take, from the perspective of executives and CTOs.

The New Norm in Development: What “1,100 Department-Optimized Courses” Signifies

The launch of Comix Academy indicates the AI education market is entering a new stage of maturity. Until now, AI training has largely fallen into two categories. One is generic courses for all employees, like “Understanding AI Fundamentals.” The other is advanced, specialized courses for training data scientists. However, the AI skills needed by most business professionals, especially in departments like sales, marketing, accounting, and HR, lie in between.

The approach of a “curriculum optimized by department” targets this niche. For a sales department, learning items might include automated generation/optimization of customer emails, data-driven enhancement of proposals, and extracting next steps from meeting analysis. For an accounting department, it could involve automated processing of invoice data, AI checks on expense reports, and automated generation of budget vs. actual reports.

The core of this approach is not teaching “AI as a technology,” but teaching “how to use AI to solve each department’s operational challenges.” Learner motivation stems not from “wanting to understand AI,” but from “wanting to make their own work easier and achieve better results.” Department-specific curricula correctly design this incentive.

How to Create a “Department-Specific AI Skill Map” for Your Company

The first step to incorporating this trend into your company is creating a “Department-Specific AI Skill Map.” Before investing in expensive external services, there’s much you can do in-house.

First, work with each department head to identify the following three points:

1. A list of routine/repetitive tasks: Email responses, data entry, report creation, simple analysis, etc.
2. The department’s core value-creation processes: For sales, it’s client meetings; for marketing, content creation; for development, design/testing, etc.
3. Current challenges and “tasks we’d do if we had time”: Data analysis, competitor research, process improvement, etc.

Next, match specific AI tools and usage methods to these items. The key here is the perspective of “using the right tool for the job,” not “using ChatGPT for everything.”

• Document Generation & Editing: ChatGPT, Claude, Notion AI
• Data Analysis & Visualization: Microsoft Copilot for Excel/Power BI, ChatGPT Advanced Data Analysis
• Image & Video Generation: Midjourney, DALL-E 3, Runway ML
• Code Generation & Task Automation: Claude Code, GitHub Copilot, Cursor

For example, a sales department skill map might include items like: “Creating industry trend reports for clients (ChatGPT + web search),” “Analyzing characteristics of high-value customers from transcribed past meeting recordings (summary/analysis with Claude),” and “Generating design improvement ideas for proposals (Canva AI + DALL-E 3).”

You can even use AI to help create this skill map. Use AI to summarize and categorize interview content with department heads, generate task lists, and suggest suitable tools. In our consulting practice, we have partially automated this process, reducing initial design effort by 70%.

How Generative AI Becoming an “Essential Sales Skill” Changes Hiring and Evaluation

The MMR Research survey indicates AI skills are becoming “mandatory requirements” for specific roles. The fact that “analytical skills” and “generative AI utilization” are listed as required skills for SaaS sales hires in 2026 signifies a shift towards a skillset that is no longer “nice to have” but “essential for hiring.”

This is changing the very definition of a sales role. Traditional sales emphasized communication, negotiation, and perseverance. However, sales in the generative AI era requires “the ability to use AI to deeply explore customer challenges and automatically generate optimal, data-driven proposals.” It’s a hybrid talent combining the high-level relationship building only humans can do with the information processing and proposal design augmented by AI.

Executives and HR leaders should consider two strategies.

First, assessing the “AI literacy” of current staff and investing in “re-education.” To what extent are staff in each department, especially customer-facing ones, currently incorporating AI into their work? Go beyond “have used it” to interview and visualize “for which tasks, which tools, and for what purpose of improving results.” Then, invest in filling skill gaps through systematic education like Comix Academy, or via in-house workshops and OJT through practical projects.

Second, revising hiring criteria and evaluation systems. In interviews for new graduates and mid-career hires, include questions about concrete experience and thinking regarding AI use. Don’t ask “Have you used ChatGPT?” but “In your past work, can you give a specific example of how you used an AI tool to improve operational efficiency?” For evaluation systems, create mechanisms to clearly recognize and reward AI-driven process improvement proposals and productivity gains achieved through AI.

Cost-Benefit Analysis: Criteria for Choosing External Services vs. In-House Development

When promoting department-specific AI education, executives are concerned about cost. Should they introduce an external training platform or build an in-house development program?

The decision criteria are “the scale requiring standardization of training” and “the degree of specialization to your company’s operations.”

• When external services are suitable: For mid-sized or larger companies wanting to efficiently spread standard basic skills to hundreds of employees. While there’s an initial investment, systematic curricula and progress management features can reduce administrative costs. Monthly fees vary by user count, but per-user costs tend to decrease with scale.
• When in-house development is suitable: For startups, SMEs, or when company processes are highly unique and generic curricula can’t cover them. While initial effort is required, you can create “hyper-practical” content integrated with your company’s tools (Slack, Salesforce, core systems, etc.). A key method is appointing internal AI power users as “AI Champions” and turning their knowledge into video content.

In a client case, building an in-house program for a ~50 person company required about 80 hours for initial design (one AI Champion’s effort) and about 40 hours for content creation. However, this reduced the estimated annual “trial-and-error time” for all employees by about 500 hours, achieving ROI within six months. ROI calculations should include not just reduced labor hours, but also revenue increases from new proposals and process improvements enabled by AI.

Beyond Operational Efficiency: Conditions for a “Winning Organization” Built by AI Talent

As Nikkei CrossTech Active asks, “Are you satisfied with just operational efficiency?” the true goal of AI utilization is creating “competitive advantage” beyond efficiency. What becomes possible for an organization staffed with people equipped with department-specific AI skills?

It is a dramatic improvement in “strategic execution speed and adaptability.” In response to market changes, sales can instantly generate and test new proposal frameworks with AI. Marketing can analyze trends and produce diverse content at explosive speed. Development can shorten product cycles by automating prototype creation and testing.

NTT DATA’s proposed “Next-Generation Architecture for Generative AI Utilization” is a concept supporting such organizational capabilities from a technical infrastructure standpoint. Importantly, alongside individual skill development, it’s crucial to design “mechanisms where the results of individual AI use accumulate and are reused as organizational assets.”

Concrete measures could include:

1. Building a Prompt Library: Create a shared database of effective AI instructions (prompts) from each department. Examples: “Prompt for analyzing high-value customer characteristics,” “Prompt for auto-generating recurring profit reports.”
2. Standardizing and Templatizing AI Workflows: Document and provide as templates the optimal workflows—which tools to use in what order—for recurring tasks (monthly reports, new customer onboarding, etc.).
3. Establishing a Data Integration Foundation: Create an environment where data for AI analysis by each department is accessible securely and efficiently. Breaking down data silos can double the effectiveness of AI use.

When this cycle of “organizational learning” begins to turn, the vision of the AI-obsessed executive connects with the frontline’s ability to execute change. The lament of “our company lacks change agents” was a reflection of the management challenge: “We have not systematically provided the skillsets and environment for executing change, tailored by department.”

Conclusion: A 3-Step “AI Talent Strategy” for Executives to Start Today

Recent trends reaffirm that AI talent development is at the core of strategic investment. To conclude, here are three concrete steps executives and CTOs can start today.

Step 1: Visualize the Current “State of Department-Specific AI Utilization”
Have brief dialogues with each department head to understand which tasks, which AI tools, and to what extent they are currently being used. If some departments aren’t using AI, explore the reasons (lack of knowledge, uncertainty in tool selection, no perceived benefit). This is the starting point for strategy.

Step 2: Collaboratively Create a “Department-Specific AI Skill Map (Phase 1)”
Based on Step 1, work with department heads to select 3-5 practical AI skills for each department to acquire within the next three months. No grand plan is needed. Start with small, tangible wins, e.g., “Sales: AI proofreading/improvement of customer emails,” “Accounting: AI classification of statement data.”

Step 3: Provide Learning Opportunities and Celebrate the First Success Stories
Provide opportunities to acquire the selected skills—external services, in-house workshops, sharing reference materials, the method doesn’t matter. What’s crucial is to publicly recognize and celebrate the first departments or individuals who achieve results and share their insights. Making success visible ignites the learning engine for the entire organization.

AI is not a technology; it’s an amplifier of human and organizational capability. The 1,100 department-specific courses and the essential skill status for sales are evidence that this amplification is now being directed toward “the real work of siloed organizations.” The competitive advantage beyond efficiency is created by an “organizational AI utilization cycle” that transcends departmental walls. Why not take that first step today?