Why Artificial Intelligence Is automating artifacts while increasing the value of professional judgment. I recently attended BARM 2026, the event organized by IIBA Italy Chapter and dedicated to Business Analysis. Although the speakers approached Artificial Intelligence from different perspectives, a common and somewhat counterintuitive conclusion emerged: AI is not reducing the value of the Business Analyst. It is fundamentally transforming the nature of the contribution Business Analysts bring to organizations. 1. The Real Limitation of AI Is Not Technology, but Context AI is proving exceptionally capable of producing content, analyzing information, generating documentation, and even developing software. However, it still exhibits a fundamental weakness: it does not truly understand the context in which it operates.  It does not know an organization's strategic priorities, political dynamics, stakeholder conflicts, corporate culture, or the trade-offs that accompany every real-world decision. As a result, while AI excels at generating answers, it still requires someone who understands the problem that needs to be solved.

2. The Business Analyst Is Moving from the "How" to the "What"

For years, Business Analysts translated business needs into requirements and specifications for developers. Today, with tools capable of generating code and documentation, that paradigm is changing. When the recipient of instructions is an AI agent rather than a human developer, ambiguity no longer creates discussion or clarification requests: it creates errors. As a result, the role is shifting from describing how a solution should be built to defining what outcome must be achieved. The focus increasingly lies on:

• objectives to be achieved
• constraints to be respected
• acceptance criteria
• operational guardrails
• expected outcomes.

The natural evolution of the Business Analyst is therefore toward governing value, decisions, and outcomes rather than specifications and documents.

3. The Value of Professional Judgment Is Increasing

One of the most interesting conclusions emerging from the event is that while AI automates many activities, it simultaneously makes human judgment even more important.

The Business Analyst of the future will not be evaluated based on the ability to produce documentation, but on the ability to:

• ask the right questions
• interpret AI-generated outputs
• make decisions under uncertainty
• mediate between competing interests
• take responsibility for decisions.

For this reason, the emerging Business Analyst is increasingly described as a Context & Value Architect: someone who creates the context within which people, processes, and technologies can generate value.

4. More AI Does Not Mean Less Business Analysis

It may seem intuitive to assume that if AI enables software to be produced faster, less analysis will be required. In reality, the opposite trend is emerging. The faster execution becomes, the more important it is to ensure that:

• the right problem is being addressed
• the context has been correctly understood
• success criteria are clearly defined
• risks and governance are adequately managed.

Reviewing and validating AI-generated outputs is becoming the new bottleneck. Productivity is increasing, but so is the importance of the experience required to govern it effectively.

5. The Real Challenge Is Building the Next Generation of Business Analysts

Perhaps the most important question is not how many Business Analysts organizations will need in the future, but what capabilities those Business Analysts will require. The automation of simpler activities may encourage some organizations to reduce junior roles. However, this approach risks being shortsighted. Operational tasks do not merely produce outputs; they also provide the pathway through which experience, relationship-building capabilities, and decision-making skills are developed. The Business Analyst of the future will need to combine three dimensions:

• strong Business Analysis competencies
• the ability to use and govern AI tools
• distinctly human capabilities such as critical thinking, leadership, ethics, communication, and decision-making.

The real challenge is therefore not replacing people with AI, but using AI to accelerate skills development and amplify the ability to generate value.

Conclusions

The most important idea that emerged from BARM 2026 can be summarized in a single statement: AI is commoditizing artifacts while increasing the value of professional judgment. Indeed:

• documents are increasingly automatable
• requirements are, at least partially, automatable
• code is becoming increasingly automatable
• context remains human
• decisions remain human
• accountability remains human.

The consequence is that the value of the Business Analyst is progressively shifting from the production of artifacts to the ability to understand context, govern the use of AI, and direct outcomes toward meaningful business value. In a world where answers are becoming a commodity, the real competitive advantage remains the ability to ask the right questions and govern the answers.