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AI Use in Project Management Nearly Doubles as Benefits Grow and Skills Gap Persists

APM finds AI now standard in UK projects: 70% use it, 29% plan to adopt, up from 36% two years ago. Gains span automation, risk, and reporting, but skills and security still lag.

2 min read
Management

AI in Project Management: Adoption Nearly Doubles in Two Years

AI has moved from pilot projects to everyday practice. New research from Association for Project Management (APM) shows 70% of project professionals say their organisation already uses AI, with another 29% planning to implement it. Just 1% report no current use or plans.

Two years ago, only 36% said their organisation was using AI, with 47% planning to adopt. The shift signals a clear message for managers: AI capability is fast becoming a standard expectation in project delivery across the UK.

Where AI Is Delivering Measurable Gains

From respondents already using AI, project teams report tangible improvements across core delivery functions:

  • Task and schedule automation: 50%
  • Resource allocation: 50%
  • Risk analysis and forecasting: 50%
  • Reporting and dashboarding: 49%
  • Stakeholder communications: 43%

Expectation has also shifted in practice: 82% say they are using AI more frequently than they anticipated five years ago.

Sentiment Has Flipped: Confidence Is High

In APM's latest survey, 62% believe the latest AI advancements will be very positive for their industry or sector, up from just 15% in 2023. The most anticipated benefits are pragmatic and immediate:

  • Freeing time for higher-value, strategic work by automating admin: 49%
  • More accurate data analysis: 43%
  • Assistance in decision-making: 42%
  • More consistent and timely reporting: 40%

Organisational support is trending the right way, with 70% confident their employer is preparing project managers for AI, and 29% saying upskilling efforts are underway. Only 1% see little preparation.

Skills, Safety, and Integration: The Real Constraints

Adoption isn't frictionless. Project professionals highlight key blockers:

  • Technical knowledge and training: 49%
  • Security and data privacy: 44%
  • Integration with workflows: 42%
  • Inaccuracy or untrustworthiness at work: 41%

As one project controls expert put it: you need to be suitably qualified and confident before using AI to generate work-because you're accountable for the output. New tools are arriving constantly, but implementing them safely at scale takes discipline and clear assurance processes.

Sector Shifts: From Hesitant to Hands-On

Across industries, adoption has surged between 2023 and 2025:

  • Construction: Already using AI in projects rose from 15% to 75%; planning to adopt is 25%; not planning dropped to 0%.
  • Engineering: Already using increased from 35% to 73%; planning to adopt is 27%; not planning is 0%.
  • Financial Services: Already using grew from 23% to 66%; planning to adopt is 34%; not planning is 0%.
  • Transport: Already using climbed from 36% to 71%.

Leadership Playbook: How to Turn Adoption into Advantage

  • Audit current AI use across projects. Map tools to outcomes (time saved, error reduction, forecast accuracy).
  • Prioritise high-yield use cases: scheduling, reporting, risk analysis, and resource optimisation.
  • Stand up an AI governance framework: data privacy, model selection, human-in-the-loop review, and audit trails.
  • Invest in targeted training by role (PMs, PMO, risk, controls). Pair tool training with quality and assurance standards.
  • Pilot with guardrails. Start small, set success metrics, and scale only after results are repeatable.
  • Integrate AI into core workflows and PMIS. Avoid orphan tools. Aim for single sources of truth.
  • Track ROI quarterly. Reallocate budget from low-impact tools to proven use cases.

Resources

Explore recent guidance and case studies from APM to align your roadmap with industry practice: Association for Project Management.

If you're building an AI skills plan for project teams, see practical training options here: AI courses by job role and popular AI certifications.

Bottom Line

AI is now standard kit in project delivery, not a side experiment. The winning move for managers is simple: focus on value-heavy use cases, upskill your teams, and put strong assurance around every AI-assisted output.

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