How Will Management Consultants Change with AI?

“Isn't management consulting a job that is difficult for AI to replace?”

They engage in dialogue with executives, organize complex management issues, and propose strategies tailored to each company.

Based on this description alone, it seems unrelated to simple automation.

However, when you break down actual consulting work, it includes a significant amount of tasks that generative AI excels at, such as information gathering, data analysis, document creation, meeting minutes, and brainstorming hypotheses.

It is not the entire profession of management consulting that AI will replace.

What will change first are the tasks that junior consultants have spent time on: “researching, organizing, and summarizing.”

To provide an outlook at the beginning

In a standard scenario, we predict that within the next 5 to 10 years, approximately 45% of the work hours currently spent by management consultants will be reduced or transferred to AI.

With a margin of error, it is roughly 35 to 55%.

This does not mean that “45% of management consultants will lose their jobs.”

It is a prediction that the same projects will be handled by fewer people in less time.

On the other hand, new types of consultations regarding AI implementation, organizational reform, business process redesign, and AI governance are increasing.

Therefore, rather than the profession itself disappearing, it is thought that the following restructuring will progress.

• Junior-level tasks centered on document creation will decrease

• The number of consultants required per project will decrease

• Value will shift from “those who propose” to “those who drive execution”

• Consultants who only speak in generalities will face a difficult environment

• The value of consultants with industry experience and specialized knowledge will rise

Management consultants will remain.

However, it is not guaranteed that the same staffing levels, fee structures, and career paths as today will persist.

Current job description of management consultants

The Ministry of Health, Labour and Welfare's job information site, "job tag," describes the work of management consultants as proposing and supporting the implementation of management strategies, organizational and personnel strategies, marketing, and operational improvements.

Specifically, this includes interviewing executives and employees, conducting site visits, analyzing information, preparing reports, formulating strategies, giving presentations, creating plans and manuals, conducting training, and monitoring implementation status.

Broadly speaking, the work can be divided into the following categories:

Work involving gathering information

This includes market research, competitor analysis, reviewing internal documents, interviews, and on-site observations.

Work involving analyzing information

This involves organizing data on sales, profits, customers, workload, organization, and human resources to identify the root causes of problems.

Work involving developing solutions

This involves creating options for new businesses, cost reductions, organizational changes, personnel systems, sales strategies, and digital transformation (DX).

Work involving summarizing into documents

This involves organizing analysis results and proposals into reports and presentation materials.

Work involving mobilizing stakeholders

This involves obtaining agreement from management, explaining plans to the front lines, and implementing reforms while managing opposing opinions.

When considering the impact of AI, it is necessary to look at these five areas separately.

Changes already taking place

[Facts currently verifiable]

Management consulting has begun to feel the impact of generative AI not just at an experimental stage, but at a practical level.

McKinsey has introduced "Lilli," a generative AI platform that searches and summarizes internal knowledge and past documents. The firm has indicated a policy of reducing time spent on information retrieval and knowledge organization to dedicate more time to problem-solving, client support, and professional development.

Accenture has also announced that by the end of August 2025, more than 550,000 employees had completed basic training in generative AI, and that it has expanded its pool of specialized talent in the AI and data fields to approximately 77,000 people.

This is not just about the addition of a new product called 'AI consulting'.

It means that the way consultants themselves work is changing to be AI-centric.

In Japan, there is also a shortage of talent to promote corporate DX. According to an analysis based on the IPA's 'DX Trends 2025', 85.1% of Japanese companies feel they lack DX talent.

While more companies want to introduce AI, they cannot handle the conceptualization, selection, operational design, and training on their own.

This gap is expected to support consulting demand for the time being.

Does AI really make consultants stronger?

[Currently verifiable facts]

In a study published in the academic journal 'Organization Science' in 2026, an experiment using GPT-4 was conducted on 758 Boston Consulting Group consultants.

For 18 consulting tasks within AI's capabilities, participants who used AI completed 12.2% more tasks, finished their work 25.1% faster on average, and improved the quality of their deliverables compared to those who did not.

However, for complex tasks that AI is not good at, the accuracy rate of participants who used AI decreased. AI users were 19% less likely to provide the correct answer than those who did not use AI.

What this study shows is not the simple idea that 'if you use AI, you will definitely become excellent'.

The text is easy to understand, logical, and persuasive.

However, the underlying analysis is wrong.

In management decision-making, this combination is particularly dangerous.

The ability to spot plausible-sounding incorrect answers will become more important for future consultants than the ability to create documents.

Tasks easily replaced by AI

From here on, these are my own predictions based on currently verifiable facts.

The percentages are not official statistics, but estimates showing how much work time will be reduced.

Information gathering and preliminary case studies

This is the work of collecting corporate information, industry trends, competitor cases, legal systems, overseas examples, and so on.

AI agents are now capable of continuously processing tasks ranging from searching, summarizing, and comparing to organizing sources.

However, private internal matters and tacit knowledge from the field cannot be obtained from public information.

Reduction in work hours after 5-10 years: 60-80%

Possibility of AI-only processing: High

Confidence level: High

Primary organization of meeting minutes and interviews

Recording, transcription, summarizing key points, extracting issues, and drafting follow-up questions are areas that are easy to automate.

On the other hand, human experience remains necessary to read between the lines regarding reasons for silence, office politics, changes in facial expressions, and the difference between what is said publicly and what is truly meant.

Reduction in work hours: 70-90%

Possibility of AI-only processing: High

Confidence level: High

Data aggregation and basic analysis

Sales analysis, customer segmentation, cost structure analysis, simple financial modeling, and graph creation will be significantly streamlined.

If the data format is standardized, AI can write analysis code, identify anomalies, and even generate explanatory text.

However, in companies where data definitions differ by department or small-to-medium enterprises where paper and Excel are mixed, manual labor will still be required for pre-processing.

Reduction in work hours: 40-65%

Possibility of AI-only processing: Medium to High

Confidence level: High

Creation of reports and presentation materials

This is the work where the impact on management consultants is most visible.

AI will handle everything from document structure, slide drafts, and charts to summaries and revisions of phrasing.

For templated market analysis or operational improvement materials, there will no longer be a need for humans to create them from scratch.

Reduction in work time: 70–90%

Possibility of AI-only processing: High

Confidence level: High

Brainstorming hypotheses and strategic proposals

AI can generate a large number of options in a short amount of time.

Tasks involving 'expanding the range of candidates,' such as new business proposals, cost-cutting plans, customer acquisition strategies, and organizational plans, will become more efficient.

However, choosing which plan to adopt requires considering factors such as the company's capital, talent, corporate culture, and even the resolve of the management.

Reduction in work time: 25–45%

Possibility of AI-only processing: Medium

Confidence level: Medium

Tasks where value increases due to AI

As AI becomes capable of creating materials, the 'work beyond the materials' will become more prominent.

Defining the real problem

The problem a client states and the problem that actually needs to be solved may not always align.

A consultation about 'wanting to increase sales' might actually stem from internal evaluation systems or departmental conflicts rather than product strength.

While AI is strong at answering given questions, finding problems that no one has yet articulated requires on-site observation and dialogue.

Conveying dissenting opinions to management

AI can create as many explanations as desired that align with a manager's wishes.

However, the value of a management consultant also lies in conveying facts that executives do not want to hear, without damaging the relationship.

Because it involves trust, courage, and ethics, this is an area where simple automation is difficult.

Coordinating interests between departments

Even an excellent strategy will not move forward if the interests of sales, manufacturing, information systems, human resources, and finance collide.

Even if it seems like an agreement was reached in a meeting, it may not be executed on the front lines.

Who is opposing it?

What are they afraid of losing?

In what order can it be accepted?

Work that deals with such organizational dynamics is considered likely to remain with humans.

Taking responsibility for execution results

In the future, it will become harder to be evaluated just for having made a 'correct proposal'.

Did sales increase?

Did inventory decrease?

Did overtime hours decrease?

Is the AI implementation being used on the front lines?

The value of the role of measuring results and revising plans will increase.

Predictions for the next 1-2 years

[Prediction]

Generative AI will become standard equipment for consultants.

Consultants who do not use AI for information gathering, meeting minutes, analysis support, and drafting slides will end up spending more time on the same work.

In the short term, rather than mass unemployment across the entire profession, the change will first appear as a gradual reduction in the number of people required for each project.

Projects that previously required six people will be handled by four to five people using AI.

Research that was previously conducted by two junior staff members will be handled by one person and an AI agent.

This is the form it will take.

On the other hand, Japanese companies are facing a shortage of DX talent, and consultations regarding AI implementation are increasing. While the number of workers using generative AI across the entire workplace is still limited, a JILPT survey shows that 57.9% of people working at companies that use AI responded that their usage has expanded compared to two years ago.

Because the increase in demand and the improvement in productivity are progressing simultaneously, the impact on employment is likely to remain difficult to see in the short term.

Current task reduction rate: 15-25%

Impact on the profession as a whole: Primarily operational efficiency

Confidence level: High

Forecast for the next 3-5 years

Systems where multiple AI agents share the workload of research, analysis, document creation, and verification will become widespread.

Consultants will shift from giving instructions to AI one by one to a role where they set the objectives, constraints, and evaluation criteria for the entire project, and supervise the results along the way.

At this stage, the staffing composition of consulting firms will begin to change.

Traditional large firms have adopted a pyramid-shaped organization with a large number of junior staff under a small number of partners and managers.

However, if the research and document creation tasks handled by junior staff decrease, the reason for maintaining the base of the pyramid with the current number of people will weaken.

While it is unlikely that new graduate hiring will be completely stopped, more companies will likely reduce hiring numbers and seek candidates who can handle client relations, data analysis, AI operation, and industry knowledge from the start.

The problem is where junior staff will gain experience.

The traditional training method of learning corporate analysis while creating documents will become less functional, and it is thought that this will shift to case studies using AI and early on-site placement.

Current task reduction rate: 25-40%

Junior staff per project: 15-30% reduction

Confidence level: Medium to High

Predictions for the next 5 to 10 years

Once AI is connected to a company's accounting, human resources, sales, customer management, and operational systems, it will be possible to analyze the business situation in real time.

Instead of collecting data once a month to create a report, the AI will estimate the cause and suggest improvements the moment a problem occurs.

If this mechanism is realized, periodic management diagnostics and general operational improvements can be handled by in-house AI and the corporate planning department without requesting external consultants.

SaaS companies, system development firms, accounting firms, and HR service companies will also likely incorporate management advisory functions into their own products.

As a result, small-scale and routine projects will be absorbed by professions and services other than management consultants.

On the other hand, problems that are difficult to decide on internally, such as corporate acquisitions, large-scale organizational reforms, entry into new markets, and withdrawal from unprofitable businesses, will remain.

The reason managers seek third-party opinions is not just a lack of knowledge.

There is also value in questioning internal conventional wisdom, maintaining distance from vested interests, and providing support for difficult decisions.

Reduction rate of current tasks: 35-55%

Personnel reduction across the profession: 10-25%

Confidence level: Medium

The impact of physical AI

Physical AI is a technology where AI operates in the real world through robots and machines.

There are not many situations where robots will directly perform the work of management consultants themselves.

However, the management challenges of client companies will change significantly.

In industries such as manufacturing, logistics, retail, construction, nursing care, and food service, the introduction of robots will necessitate the restructuring of personnel allocation, capital investment, store design, safety management, training, and evaluation systems.

A survey by the World Economic Forum also shows that many companies consider robots and automation, in addition to AI and information processing technology, as factors for business transformation.

If it is just a matter of choosing technology, robot manufacturers and system companies can handle it.

What will remain for management consultants is the work of designing 'how to transform the entire company using that technology'.

In the long term, the boundaries between management consultants, business consultants, and engineers will likely become even thinner.

The impact differs between large companies and small to medium-sized enterprises.

Large consulting firms

Large firms possess past project materials, industry data, expert networks, and proprietary tools.

By combining these with generative AI, they can build high-performance internal AI.

The larger the firm, the easier it is to advance productivity improvements through AI; while they can reduce the number of junior staff, they are also in a position to easily win large-scale projects for AI implementation and company-wide reform.

A situation may arise where 'the company grows, but the number of people assigned to a single project decreases'.

Small to medium-sized and specialized firms

Companies that only sell general market research or strategy documents will face intense competition from the AI of large firms and low-cost services.

On the other hand, there are opportunities for companies with deep knowledge of specific fields such as healthcare, manufacturing, logistics, food and beverage, local businesses, and business succession.

This is because even a small team can secure an amount of analysis comparable to large firms by using AI.

Independent consultants

Independent consultants will be able to handle a large amount of work on their own without outsourcing research or document creation.

However, the number of clients willing to pay high fees for general theories that AI can generate will decrease.

It will be necessary to have a track record, a relationship of trust with management, industry connections, and the ability to handle execution support.

Impact on full-time employees, junior staff, and freelancers

Among full-time employees, the impact differs between managers and above versus junior staff.

While those responsible for client relationships, contracts, proposals, and team management are relatively likely to remain, junior staff with a high ratio of research and document creation work will be more affected.

For freelancers, the unit price for work that only involves research, document creation, and data organization will likely decline.

Conversely, those with experience in specific industries, former business leaders, those with AI implementation experience, and those who have successfully completed reform projects will find it easier to gain demand as leaders of small-scale projects.

Regional differences will also emerge.

In urban areas, large-scale projects and AI-specialized projects will increase.

In regional areas, it is necessary not only to introduce AI tools but also to talk face-to-face with managers and on-site employees to provide support for integrating them into existing operations.

Even with the 2026 digitalization and AI implementation subsidies, support for implementation by small and medium-sized enterprises continues, and the demand for hands-on support for regional companies will not disappear anytime soon.

Three scenarios: Standard, Optimistic, and Pessimistic

Standard Scenario

40-50% of current tasks will shift to AI, and the number of people per project will decrease.

Because the demand for AI implementation and business transformation will increase, the industry as a whole will not shrink rapidly.

However, personnel structures centered on young staff will be reviewed, and the prices for general research and strategy projects will decrease.

Personnel change in 5-10 years: 10-25% decrease

Confidence level: Medium to High

Optimistic Scenario

AI will lower consulting fees, allowing small and medium-sized enterprises that could not afford them before to use them.

A small number of consultants will support many companies, and demand for AI reform, business redesign, education, and governance will expand.

Even if the workload per project decreases, the number of clients will increase, and employment will be maintained or increased.

Personnel change in 5-10 years: Flat to 15% increase

Confidence level: Medium

Pessimistic Scenario

Enterprise AI will constantly analyze internal company data, and departments such as corporate planning, system companies, accounting, and human resources will absorb advisory tasks.

It is becoming common for executives to consult AI directly, reducing the reasons to use external consultants for general strategy formulation and operational improvements.

Even at large firms, hiring of junior staff will decrease significantly, and small-to-medium firms with weak expertise as well as independent consultants will be weeded out.

Current task reduction rate: 60-75%

Personnel change in 5-10 years: 30-50% decrease

Confidence level: Low to Medium

Potential new roles that may emerge

While some jobs will decrease due to AI, new roles will also be created.

AI Business Transformation Consultant

Beyond just introducing AI tools, they will redesign organizations, operations, evaluation systems, and authority structures.

AI Governance and Risk Officer

They will manage issues such as incorrect answers, discrimination, copyright, personal information, confidential data, and accountability.

The Ministry of Economy, Trade and Industry and the Ministry of Internal Affairs and Communications have updated their AI business guidelines, and companies also need systems to use AI safely.

AI Output Verification Consultant

They will verify market analyses, financial models, contractual assumptions, and management proposals generated by AI.

Human-AI Workflow Designer

They will design which tasks should be handled by humans and which should be delegated to AI agents.

Physical AI Implementation Support Specialist

They will support the introduction of robots in factories, warehouses, and stores, including investment returns and staffing arrangements.

Execution-Accountable Consultant

Instead of just delivering reports, they will share responsibility with the client until performance metrics are achieved.

Even if the name changes, the function of organizing management issues and mobilizing organizations will remain.

Skills to acquire from now on

The ability to verify AI responses

Knowing how to write prompts is not enough.

You need the ability to verify sources, reproduce calculations, question premises, and compare with alternative hypotheses.

Deep knowledge of specific industries

While AI is strong at general theories, it cannot fully grasp industry-specific business practices, regulations, on-site processes, or customer psychology.

Specialization, such as being an expert in cost improvement for the manufacturing industry, will be more advantageous than being a generalist in management.

Problem-setting ability

As the value of the ability to create answers decreases, the value of knowing what to ask increases.

You need an attitude of not accepting the problems presented by clients at face value.

Facilitation and negotiation

This is the ability not just to lead meetings, but to draw out opposing opinions, organize interests, and find points of agreement.

Execution and effectiveness measurement

Instead of finishing by delivering a proposal, you must design execution plans, assign personnel, set deadlines, and define metrics.

It is important to make your track record based on the results you changed, not just the content you proposed.

Knowledge of handling AI and personal information

You must not input client documents or employee information into external generative AI without permission.

The Personal Information Protection Commission also warns that when inputting personal information into generative AI services, you should check the purpose of use and how the service provider handles the data.

Concrete actions that current employees can take

First, try recording your work for one week.

How many hours are you spending on research, analysis, document creation, meetings, client correspondence, and on-site support?

From those, choose one task that can be reduced by half or more using AI.

For example, for market research, make the process from searching, summarizing, and organizing sources to drafting comparison tables into a single workflow.

Next, do not use the time you saved to increase the number of pages in your documents.

Use it for additional client interviews, on-site observation, hypothesis testing, and execution support.

Then, decide on one area of expertise for yourself.

Aim to be in a position where you can explain not just the broad title of 'strategy consultant,' but whose problems you can solve and which ones they are.

For young professionals and those looking to change jobs, simply highlighting that you can create documents using AI will make it difficult to differentiate yourself.

It is more effective to build experience in verifying AI analysis, moving people on-site, and improving numerical results.

Possibility of inaccurate predictions and opposing views

There are uncertain parts in the predictions made so far.

First, there is the case where AI performance improves faster than expected.

If audio, video, internal company data, and on-site sensors are integrated, AI might even process parts of interviews and on-site observations.

In this case, the 45% reduction forecast would be too low.

Second, there is the case where companies do not trust AI judgments.

If issues such as confidential information, incorrect answers, and the location of responsibility persist, and operations continue to place humans in the final decision-making role, automation will be delayed.

Third, there is the case where demand for consulting increases significantly.

Issues that managers must address, such as AI, population decline, business succession, geopolitics, cybersecurity, and decarbonization, are increasing.

Even if productivity per person increases due to AI, if the number of consultations increases even more, the number of personnel will not decrease.

Fourth, there are economic factors other than AI.

The consulting industry is influenced by corporate investment appetite and economic downturns.

Even if there is a decline in future hiring, it will not necessarily be due solely to AI.

Summary

Management consultants are not a special intellectual profession that will not be replaced by AI.

A significant portion of current tasks, such as research, analysis, meeting minutes, and document creation, overlaps with AI capabilities.

In a standard scenario, we predict that approximately 45% of current work hours will be reduced or delegated within 5 to 10 years.

Particularly affected are the preliminary research and document creation tasks that have been handled by junior staff.

On the other hand, defining problems, building trust with executives, internal coordination, implementation support, and taking responsibility for results will remain.

What will decrease in value from now on is not the person who possesses a lot of knowledge, but the person who merely organizes public information to create generic proposals.

What will increase in value is the person who, while using AI, also questions it, identifies company-specific problems, and can mobilize the field.

Management consultants will not disappear.

However, the core of the profession will shift from 'thinking and delivering documents' to 'combining AI and humans to realize transformation.'

*This article is a prediction based on materials and technical trends available at the time of research. It does not guarantee future employment, technological progress, or corporate hiring policies. The work reduction rates and personnel change rates are not official future statistics but independent estimates based on a breakdown of job content.