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Market Impact
A FORRESTER CONSULTING Thought Leadership STUDY Commissioned by miro, November 2025
Market Impact
A FORRESTER CONSULTING Thought Leadership STUDY Commissioned by miro, November 2025
No matter where an organization is on its AI journey, people lie at the heart of this transformation.1 Teams of people must collaborate effectively to do their jobs and achieve their organization’s goals. As AI technology and collaboration tools become increasingly common, teamwork should be easier and more productive than ever. However, most firms are struggling to derive meaningful returns on their investments. Technology silos, a lack of cross-functional alignment, and AI tools focused on individual rather than team productivity are inhibiting consistent collaboration and organizations’ ability to achieve their objectives.
AI has the potential to strengthen teamwork and collaboration in addition to enhancing overall productivity. Focusing AI implementations on digital canvases can improve teamwork and handoffs and better connect goals to execution. In doing so, leaders can achieve key goals including enhancing customer experience, increasing revenue, and optimizing time to value — all while employees find more freedom to focus on creative, strategic work.
In September 2025, Miro commissioned Forrester Consulting to evaluate AI integrations and workflows for team innovation. Forrester conducted an online survey of 518 decision-makers across engineering and product design, IT, and lines of business to explore this topic. We found that while AI has the potential to enhance teamwork, current deployments often focus too much on individual productivity. However, we discovered that AI-enhanced canvas-based workspaces can be a key element of improving collaboration, connecting goals to execution, and accelerating time to value.
Leaders’ top priorities include improving collaboration and the impact of their AI investments. Nearly 90% of decision-makers said improving collaboration and focusing AI on the most impactful use cases and workflows are critical to achieving their organization’s top goals, which include growing revenue and improving time to value.
Current AI tools focus too much on individual productivity. Despite cross-organizational AI implementations, firms are struggling to find transformative value in their current deployments. Eighty-two percent of respondents were interested in AI solutions that drive team — not just individual — productivity.
AI boosts collaboration when integrated with tools where teamwork happens. Fifty-four percent of decision-makers saw the potential of AI to enhance teamwork and collaboration. With teamwork increasingly happening on visual collaboration tools, 83% of respondents were interested in using shared, canvas-based workspaces with AI enhancements to improve collaboration.
Product development teams are at the forefront of transforming workflows with AI. Most surveyed product development leaders said their organizations are currently integrating or planning to integrate AI capabilities across the innovation cycle with customer/user journey mapping, roadmap management, and cloud infrastructure design among top planned deployments.
Surveyed decision-makers’ top organizational goals over the next 12 to 24 months included growing revenue (56%), as well as improving time to value (53%), customer value (52%), and time to market (52%). To achieve these goals, leaders are focused on strengthening collaboration and refining AI strategies. Without a connection to strategic business goals and support from a broad array of stakeholders, AI experiments are too small and localized to produce impact that matters to the enterprise.2 AI integrations that encourage and enhance teamwork and collaboration, which are critical to organizational success, can demonstrate greater impact. Our survey uncovered the following:
Teamwork and collaboration must be improved to achieve organizational goals. Eighty-nine percent of respondents said that improving collaboration and teamwork is key to achieving their organizational goals; of those, 42% said it was critical (see Figure 1). Since teamwork and collaboration are top drivers of success across an enterprise, integrating AI across these workflows can demonstrate its transformational potential.
AI implementations will focus on the most impactful use cases and workflows. Leaders that succeed take a disciplined approach to AI implementation. They align AI strategy with business goals, communicate its full value across the enterprise, and prioritize foundational capabilities for reuse and scale.3 For 88% of decision-makers, focusing on the most impactful use cases and workflows is important, with 43% seeing it as a critical need. Product development is one key area of impact, with product, engineering, and design leaders indicating they have currently integrated AI capabilities in areas such as technical documentation (50%), technical design/diagramming (46%), and customer/user journey mapping (45%), insights and feedback (42%), and concepting/prototyping (41%).
Click to see data by business unit
Base: 518 cross-functional product design, IT, and LOB decision-makers for SaaS purchasing currently or planning to integrate AI into workflows
Note: Showing top five “Critical” results; individual percentage values may not sum to totals due to rounding
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Select one
Organizations are increasingly using digital canvases alongside more traditional collaboration tools. Seventy-nine percent of respondents reported that their organization’s use of visual collaboration tools like digital canvases has increased in recent years. More than four in 10 (43%) also reported that these tools were critical to their organization’s workflows, of similar importance to more traditional touchpoints like chat and document co-creation (see Figure 2).
Click to see data by business unit
Base: 518 cross-functional product design, IT, and LOB decision-makers for SaaS purchasing currently or planning to integrate AI into workflows
Note: Showing top five “Critical” results.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Select one
of decision-makers said their organization’s use of canvas/digital whiteboard tools has increased in recent years alongside the use of more traditional collaboration tools.
Despite the importance of collaboration in most employees’ workdays — and, as detailed above, for organizations’ success — it is becoming more complex and less effective with new technologies, including AI, disrupting it further. Work is more fragmented, especially as hybrid work and distributed teams have become the norm, and technology now inhibits rather than enables cross-functional collaboration. Knowledge gets lost, questions are repeated, and productivity lags as people navigate between multiple collaboration tools. Tech stacks should make collaboration and prioritization easier, but decision-makers and their teams are experiencing the consequences of complex, siloed technology:
Key determinants of success are also top challenges. Although identifying and prioritizing the right problems to solve is a top factor in organizational success, nearly half (46%) of respondents reported that difficulty prioritizing initiatives is an impediment in their department (see Figure 3). Improving cross-functional collaboration was critical for attaining goals, but 43% of respondents noted that current technology inhibits it. Finally, 45% saw too much time spent on task work rather than creative, strategic work. This indicates that something is amiss in current ways of working — workflows and tech stacks are not enabling teams to focus on the impactful work that contributes to organizational success.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Current AI tools focus too much on individual productivity and point solutions. Top challenges imply — and even directly — identify current technology as an inhibitor rather than an enabler of success. Organizations are struggling to realize the promises of AI to reduce task work, enable cross-functional alignment, and speed up time to value. Instead, 75% of respondents felt that most AI tools focus too much on individual, rather than team, productivity. Thirty-nine percent said this individual emphasis negatively impacts returns on their organization’s AI investments (see Figure 4). Respondents also felt that AI is mostly implemented as a point solution rather than embedded in of their core work tools (35%). Furthermore, 69% agreed that switching between core work tools and AI tools creates friction and interrupts workflows, once again indicating that the two should be united rather than kept separate. Uncertainty around which use cases to target with AI rounded out respondents’ top three factors impacting returns (33%).
of decision-makers agreed that most AI tools focus too much on individual productivity rather than team productivity.
Select one
Click to see data by business unit
Base: 518 cross-functional product design, IT, and LOB decision-makers for SaaS purchasing currently or planning to integrate AI into workflows
Note: Showing top five responses.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Product development and IT leaders were more likely to note the impact of these factors on ROI compared to other business leaders (see Figure 5). Forty percent of IT leaders and 44% of product development leaders agreed that AI is implemented for individual productivity compared to other business leaders (31%). Likewise, 38% of IT leaders and 39% of product development leaders saw AI’s implementation as point solutions rather than being integrated into core work tools as an ROI inhibitor, compared to 26% of other business leaders.
Select all that apply
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Cross-functional product teams also contend with ambiguity and misalignment. Engineering, product, and design leaders also pointed to a lack of clarity in tying product goals to revenue impact (51%). Misalignment slowed down or completely blocked execution for 44% of respondents, while a lack of focus on both customer problems (44%) and product vision (39%) also impeded workflows. These challenges inhibited their organizations’ ability to attain their critical goals of increasing efficiency, prioritizing the right products to build, and increasing speed of development and iteration cycles.
People-centric challenges hinder AI success. AI is innately connected to human users, and their experiences with it are a principal factor in its success or failure.4 Instead of primarily viewing AI deployment as a technology and data exercise, it must also be framed in a way that reinforces positive practices, beliefs, and behaviors of those who use it.5 The leaders we surveyed reported a lack of technical skills (37%), difficulty keeping up with the pace of change (36%), and a reluctance to shift existing workflows to integrate AI (36%) as their top three AI implementation challenges (see Figure 6). These reported gaps in employee readiness and reluctance to change can create significant barriers to success.
Click to see data by business unit
Base: 518 cross-functional product design, IT, and LOB decision-makers for SaaS purchasing currently or planning to integrate AI into workflows
Note: Showing top five challenges.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Despite current challenges, decision-makers believe in AI’s potential to enhance results and outcomes. In addition to productivity, they also see the potential for AI to enhance knowledge and insights, teamwork and collaboration, and even creativity. To realize these outcomes, leaders are refining their AI implementations. In doing so, they are considering AI solutions that enable them to resolve their top organizational challenges, especially around collaboration.
Our survey uncovered the following insights regarding decision-makers’ plans for using AI, including in canvas-based workspaces, to improve teamwork:
Select one
AI solutions should boost collaboration, embed context, and prioritize user experience. Respondents noted an understanding of the importance of collaboration to organizational success and the potential of AI to help maximize it, with 82% being interested in AI solutions that drive teamwork and collaboration. Context is especially important, as many project workflows are cross-functional and multifaceted. With context-rich prompting, employees can quickly incorporate all project materials into a prompt to improve AI outputs and make meaningful progress on projects. Respondents said AI solutions that make it easy to include project materials and context in prompts (82%) and tap into all project materials and context to answer prompts (84%) are top requirements in the future. In addition, 83% are prioritizing user experience features like less prompting effort and the ability for users to select their own large language models.
of respondents were interested in AI solutions built on shared, canvas-based workspaces.
Shared, canvas-based workspaces with AI enhancements can ease challenges. As noted earlier, the use of canvas-based workspaces has significantly increased in recent years (see Figure 7). Respondents were particularly interested in those that integrate AI solutions (81%). They saw the potential of these shared workspaces to solve their top challenges and want to use them to improve cross-functional collaboration and handoffs (83%) and better connect goals to execution (82%).
Click to see data by business unit
Base: 518 cross-functional product design, IT, and LOB decision-makers for SaaS purchasing currently or planning to integrate AI into workflows
Note: Showing six of 11 choices.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
Focused and targeted AI capabilities can produce expansive benefits. AI has the potential to enhance work and outputs across organizations and functions. From accelerating product development workflows to automating tedious tasks to improving and personalizing communications, AI investments can drive success.6 The surveyed decision-makers saw or anticipated a range of benefits at the broader business level and at the employee and workflow level. Their top business benefits included improved customer experience (CX) (52%), increased revenue (49%), and increased efficiency and time to value (46%) (see Figure 8). These benefits mirror many of decision-makers’ top organizational goals, presenting an opportunity to demonstrate the impact of AI on their organizations.
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
The potential workflow and employee benefits of AI expand upon these business benefits to demonstrate impact that can be seen and experienced regularly, even daily. Fifty-four percent of surveyed leaders said their organization is currently seeing or expects to see increased employee freedom to focus on strategic work (see Figure 9). This demonstrates that AI is viewed as an enhancement — not a replacement — for the people and teams that drive a business. Additional benefits included increased productivity of individuals and teams (51%), more automation of repetitive/manual tasks (51%), and increased cross-functional collaboration (48%).
Source: Forrester's Q3 2025 AI Workflows For Human Innovation Survey [E-65113]
When business leaders expand their workforce AI deployment beyond a technology and data exercise and include the teams it will benefit, they set themselves up to drive both employee experience and business success.7 The surveyed decision-makers saw the potential of AI to help them overcome challenges and enhance collaboration and teamwork, understanding that in doing so, their employees and their businesses can reap significant benefits.
As a result, they expected business, workflow, and employee benefits to demonstrate the value of this strategy. Leaders today must focus on removing blocks and challenges that block the benefits they can receive from AI implementation.
of decision-makers believed AI will increase employees’ ability to focus on creative, strategic work, both individually and collaboratively.
Forrester’s in-depth survey of 518 global product development, IT, and other business decision-makers on how their organizations are integrating AI into individual and team workflows yielded several important recommendations:
In this study, Forrester conducted an online survey of 518 cross-industry product development, IT, and other business decision-makers based in North America, Europe, and the Asia-Pacific to evaluate current and planned AI use cases for team productivity. All respondents were interested in or currently integrating AI into at least one departmental workflow. Respondents were offered a small incentive as a thank you for time spent on the survey. The study began in August 2025 and was completed in September 2025.
| Company HQ | % |
|---|---|
| Europe | 39% |
| North America | 31% |
| Asia-Pacific | 30% |
| Number of Employees | % | |
|---|---|---|
| 20,000 or more | 6% | |
| 5,000 to 19,999 | 11% | |
| 1,000 to 4,999 | 27% | |
| 500 to 999 | 38% | |
| 100 to 499 | 9% | |
| 2 to 99 | 8% | |
| Business unit | % |
|---|---|
| IT | 35% |
| Engineering and product development | 33% |
| Line of business | 32% |
| Respondent title | % | |
|---|---|---|
| C-level executive | 19% | |
| Vice President | 37% | |
| Director | 44% | |
Related Forrester Research
AI At The Table: A New Era Of Intelligent Meetings, Forrester Research, Inc., September 23, 2025.
The Future Of Work Requires A Better Collaboration Model, Forrester Research, Inc., July 17, 2023.
Generative AI Prompts Productivity, Imagination, And Innovation In The Enterprise, Forrester Research, Inc., February 10, 2023.
Generative AI: What It Means For Design, Forrester Research, Inc., July 7, 2023.
Ground Your Workforce AI Strategy In Human Experience, Forrester Research, Inc., March 6, 2025.
How To Design An Effective Learning Strategy For Workforce Generative AI, Forrester Research, Inc., December 12, 2024.
Prepare Your Workforce For Disruptive Technology Change, Forrester Research, Inc., May 22, 2025.
Additional Resources
Frederic Giron, 1+1+AI=5: How Generative AI Is Empowering Teams, Forrester Blogs.
J. P. Gownder, Build A Human-Centered Productivity Strategy, Forrester Blogs.
J. P. Gownder, Your Employees Aren’t Ready For AI — Prepare Them With AIQ, Forrester Blogs.
June 13, 2024, GenAI Productivity Gains For Employee- And Customer-Facing Teams, Webinar.
ref1 Source: Ground Your Workforce AI Strategy In Human Experience, Forrester Research, Inc., March 6, 2025.
ref2 Ibid.
ref3 Source: Align AI Strategy And Value To Maximize Your Investments, Forrester Research, Inc., July 2, 2025.
ref4 Source: Ground Your Workforce AI Strategy In Human Experience, Forrester Research, Inc., March 6, 2025.
ref5 Ibid.
ref6 Source: Generative AI Prompts Productivity, Imagination, And Innovation In The Enterprise, Forrester Research, Inc., February 10, 2023
ref7 Source: Ground Your Workforce AI Strategy In Human Experience, Forrester Research, Inc., March 6, 2025.
This study was conducted by Forrester’s Custom Content Consulting Practice. Get in touch to discuss your custom content needs and goals. Learn more about all of Forrester's consulting capabilities.
Rachel Baum, Market Impact Consultant
Contributing Research:
Forrester’s Future Of Work research group
November 2025
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