AI Adoption in Professional Services 2026: Benchmark of 2,535 Professionals

How 2,535 people in professional services use AI at work: how far along they are, what holds them back, the tools they use and what leaders do differently.

The AI Report benchmark · 2,535 people · Updated November 2, 2026

AI in professional services: 13% are leaders: AI rolled out to their team or company (All respondents: 14%).

We asked 2,535 people who work in professional services how they use AI at work. They answered The AI Report’s Where You Stand benchmark between July 20, 2026 and November 2, 2026. Here is how far along they are, what holds them back, what they want from AI next and which tools the most advanced teams use, compared with all 14,452 people in the benchmark.

62%
are still early: just exploring or testing a few tools
All respondents: 63%
13%
are leaders: AI is rolled out to their team or used across their company
All respondents: 14%
31%
say their biggest blocker is picking the right tools
All respondents: 32%
39%
want AI to help them save time in the next 90 days
All respondents: 40%

Key findings

  • People in professional services are behind everyone else in the benchmark. 13% are leaders, against 14% of all respondents, and 62% are still early.
  • The biggest blocker is picking the right tools (31%), almost tied with the skills gap (31%). More people here name results they can't trust: 7% against 6% across the benchmark.
  • Their top goal is to save time (39%). More of them than average want to grow revenue: 17% against 14%.
  • ChatGPT is the most used AI tool (77% of those who named a tool), then Claude (72%) and Gemini (49%).
  • Leaders lean on Claude. 83% of leaders use it, against 65% of those still early.

How far along people in professional services are with AI

The largest share of people in professional services say they are “just exploring” (33%). 7% say AI is used across their company and 5% are rolling it out to their team.

Professional services
All respondents
  • Just exploring
  • Testing a few tools
  • Using 1 to 3 tools for real
  • Rolling out to their team
  • Used across the company
  • Helping others with AI

What holds people in professional services back

We asked for the single biggest blocker. Picking the right tools leads at 31%. If that is you too: shortlist tools by the job you need done.

Picking the right tools
31%all 32%
Skills gap
31%all 30%
No time
14%all 15%
Results they can't trust
7%all 6%
Budget
6%all 6%
AI moves too fast to keep up
4%all 5%
Security or legal concerns
3%all 3%
Tools didn't stick
2%all 2%
Getting the team on board
1%all 2%
  • Professional services
  • All respondents

What they want from AI in the next 90 days

39% want to save time, 29% want to build their AI skills and 17% want to grow revenue.

Save time
39%all 40%
Build AI skills
29%all 28%
Grow revenue
17%all 14%
Build an AI product
9%all 9%
Make better decisions
4%all 5%
Cut costs
2%all 2%
Ship faster
under 1%all 2%
  • Professional services
  • All respondents

The AI tools people in professional services use

People named 3.3 AI tools each on average. These are the 12 most used, as a share of the 2,333 people here who named at least one. Compare any of them in our AI tool database.

ChatGPT
77%all 79%
Claude
72%all 69%
49%all 47%
Canva
24%all 24%
18%all 16%
17%all 16%
Microsoft Copilot
14%all 12%
5%all 5%
Salesforce
5%all 6%
Power BI
5%all 7%
Otter
4%all 4%
4%all 4%
  • Professional services
  • All respondents

What the leaders use differently

Leaders are the 319 people in professional services whose AI is rolled out to their team or used across their company. They named 3.8 tools each, against 2.9 for the 1,581 who are still early. These are the clearest differences.

ToolLeadersEarlyGap
Claude83%65%+18 pts
Microsoft Copilot19%10%+10 pts
Perplexity23%16%+7 pts
HubSpot8%3%+5 pts
Salesforce8%3%+5 pts
  • Share of each group who use the tool. Leaders: 305 people, early: 1,413 people.

Where they use AI at work

Writing comes first (70%), then research (58%) and personal productivity (58%). People could pick several areas.

70%all 69%
58%all 54%
33%all 34%
32%all 32%
26%all 22%
Operations
24%all 24%
19%all 21%
19%all 21%
Product
18%all 19%
  • Professional services
  • All respondents
  • Asked July 20 to August 31, 2026: 1,072 answers.

Budget for a first AI project

36% are not sure yet. The most common amount named is under $500 (42%).

Under $500
42%all 37%
$500 to $5K
13%all 12%
$5K to $25K
6%all 6%
$25K to $100K
3%all 3%
$100K+
1%all 2%
Not sure yet
36%all 40%
  • Professional services
  • All respondents
  • Asked from September 1, 2026: 1,467 answers.

Who answered

61% decide, recommend or have a say in what their company buys.

Company size

Just me
46%all 35%
2 to 10
20%all 16%
11 to 50
9%all 10%
51 to 200
7%all 11%
201 to 1,000
6%all 9%
1,001 to 5,000
5%all 7%
5,000+
8%all 13%
  • Professional services
  • All respondents

Role

Executives and founders
27%all 23%
Directors
13%all 17%
Managers and team leads
17%all 21%
Individual contributors
20%all 22%
Consultants and advisors
21%all 13%
Students and career switchers
1%all 4%
  • Professional services
  • All respondents

Say in what their company buys

Decide what to buy
37%all 27%
Not involved
20%all 27%
Buy just for themselves
19%all 20%
Recommend what to buy
13%all 14%
Have some say
12%all 12%
  • Professional services
  • All respondents

What leaders told The AI Report podcast

“We figured that it was better to go more narrow and deep and really scale agents on what is our core process, which is recruitment.”

Denis Machuel, CEO at The Adecco Group. Adecco started with AI pilots scattered across the business, then switched to going narrow and deep: it picked its core process, recruitment, and scaled agents there first. If your pilots are spread thin, choose the one workflow that drives the business and go deep on it. Watch or read the episode.

“We want our AI to know everything, not just one slice of the overall financial picture.”

Braden Warwick, Financial Planning Product Architect at PWL Capital. Connect your data before you buy more AI point tools. PWL Capital had already joined up its CRM, onboarding, planning and portfolio data in a data lake, so it is building its own meeting-notes tool designed to draw on each client's full picture, instead of adding one more vendor plugin that only knows a single slice. Watch or read the episode.

“You're not even actually looking for perfection. You're actually looking for improvement.”

Jason Li, CTO at Laurel. Before deciding what to automate, find out where time actually goes. Laurel captures real activity data rather than surveys, sorts it into the firm's own categories of work, and flags repeatable, low-judgment tasks like data entry and document assembly. Leaders can then decide whether the fix is a new hire or an AI tool, for example when senior partners are losing hours to internal admin instead of winning clients. Watch or read the episode.

Next steps

The AI Report benchmark

How do you compare?

Answer the same nine quick questions as these 14,452 people. See which of five AI types you are, how you compare with readers like you, and get a free 30-day AI roadmap by email.

Free. You also get The AI Report, the five-minute AI briefing, every weekday. Unsubscribe anytime.

Compare with other groups

The full benchmark: AI at Work Benchmark 2026, with every industry, role and company size side by side.

By industry: Healthcare, Software and tech, Education, Marketing and media, Manufacturing, Nonprofits and government, Financial services, Retail and e-commerce, Real estate, Legal.

By role: Executives and founders, Directors, Managers and team leads, Individual contributors, Consultants and advisors, Students and career switchers.

By company size: Solo professionals, Small businesses (2 to 50), Mid-size companies (51 to 1,000), Large enterprises (1,001+).

About this data

These numbers come from The AI Report’s Where You Stand benchmark. Between July 20, 2026 and November 2, 2026, 14,452 people completed it. This page covers the 2,535 who said they work in professional services.

  • Answers are self-reported. People chose their own industry, role, company size and stage.
  • “Early” means just exploring or testing a few tools. “Leaders” means AI is rolled out to their team or used across their company.
  • People could pick more than one tool, so tool shares add up to more than 100%. Tool shares are out of the 2,333 people here who named at least one tool.
  • Where people use AI was asked from July 20 to August 31, 2026 (1,072 answers here).
  • Budget was asked from September 1, 2026 (1,467 answers here).
  • Percentages are rounded to whole numbers.
  • We never publish individual answers. A group only gets a page with 100 or more people, and we only compare groups of 30 or more.
  • People who take an AI newsletter's quiz are more interested in AI than the average worker, so read these numbers as a benchmark of people actively working on AI, not a national average.

Last updated November 2, 2026. To cite this page: The AI Report, AI at Work Benchmark 2026, theaireport.ai/tools/benchmark.