CRP 2026: Participant Voice
Quantitative results tell us what respondents experienced; the open-ended feedback tells us how they talk about it. The numbers and quotes below are derived from the frozen N=200 CRP dataset and will not change. 162 of 200 respondents (81%) wrote something in the optional Q74 feedback box. Some wrote a single word; one wrote nearly 700 characters. This page surfaces what they said.
Prompt as shown to respondents: “Open-ended feedback on the survey itself or on technology adoption barriers.”
Engagement at a glance
Engagement was high but uneven: about a third of responses added new substantive content, a third were brief affirmations of the survey itself, and a third were short “no further comment” placeholders. The numerical-result pages report on what the survey asked; this page reports on what respondents felt was missing or worth elaborating.
How much did people write?
Length is a useful engagement signal. Short responses tend to be courtesy (“thanks”); medium and long responses are where the real content lives.
| Length bucket | Responses | % of feedback |
|---|---|---|
| Micro (≤ 10 chars) | 38 | 23% |
| Short (11–50 chars) | 29 | 18% |
| Medium (51–200 chars) | 55 | 34% |
| Long (201–500 chars) | 28 | 17% |
| Essay (> 500 chars) | 12 | 7% |
The 12 mini-essays (each over 500 characters) are highlighted on their own below — they read like talk-aloud reflections rather than survey answers, and several anticipate themes we plan to investigate in the next survey iteration.
What did they talk about?
Each response was tagged with one or more theme labels via a regex categorizer; one response can match multiple themes. Themes ranked by frequency:
| Theme | Responses | % of 162 |
|---|---|---|
| "You covered everything" | 35 | 22% |
| No additional comment | 24 | 15% |
| Workforce skills & training | 16 | 10% |
| Leadership, culture, change | 14 | 9% |
| Praise / thanks | 11 | 7% |
| Budget & cost | 10 | 6% |
| Sector-specific concern | 9 | 6% |
| AI / ML adoption | 7 | 4% |
| Legacy systems & integration | 6 | 4% |
| Pace of change | 5 | 3% |
| Survey scale design | 4 | 2% |
| Role-specific concern | 4 | 2% |
| Vendors & third parties | 3 | 2% |
| Cloud / SaaS | 2 | 1% |
| Security & compliance | 2 | 1% |
| Strategy / vision | 1 | 1% |
| Found a question confusing | 1 | 1% |
| Wanted more questions on... | 1 | 1% |
Mini-essays
Long-form responses where the participant treated the feedback box as a place to think out loud. These are the closest thing the dataset has to interview transcripts.
“First of all, very interesting survey questions and topic areas. I think my organization might be similar to many others in the software field. We develop lots of cutting edge technology like AI in our products, however adopting the same types of things into the systems we use internally is a bit more problematic. There is pressure to adopt more technology to achieve more organizational efficiency but we struggle to come up with ways to identify the right systems and how to measure the ROI. We have ended up with fragmented use cases of new technology that never should have been purchased without doing a proof on concept to see if it will do what we need it to organization-wide. I think more organizations are getting pressure from all different levels to integrate something with AI. The issue is many of the AI use cases haven't demonstrated consistent ROI. My particular area is AI related and we focus on very specific usage within our product. Going out and buying some new technology that says it has AI capability can be quite a leap of faith unless it is an established vendor.”
“One of our biggest barriers to implementing new technologies has to do with organizational culture as it pertains to "generations" across the organization. A lot of our older members of leadership get excited about and push new technology onto our workforce. Our older members tend to be management, and our younger workforce is more technical. Therefore, the younger folks tend to perceive new tech with a lot of skepticism and reticence. When leadership pushes or forces it, they become more skeptical. We need to do a better job of getting buy in from our tech savvy younger workforce, or should take their lead in terms of pursuing technology. One past issue we've had is our young technical workforce making recommendations, then older Boomer leadership being unwilling to learn it or purchase an enterprise license, even though all of the technical staff wanted it. It is an issue when management pushes less effective tools and fails to adopt useful tools, and when management thinks it knows better than the actual master's and PhD level experts on the ground floor.”
“Many surveys overlook deeper organizational realities that strongly affect technology adoption, such as change fatigue from too many simultaneous initiatives, unclear role-specific use cases, and misalignment between incentives and desired behaviors. Factors like data quality and governance, integration challenges with legacy systems, and the presence of informal influencers can also quietly hinder success. Additionally, true readiness depends on continuous feedback loops, meaningful skill development (not just one-time training), and a culture that supports experimentation without fear. Without accounting for these human, cultural, and operational dimensions, assessments of adoption maturity often appear stronger than they actually are.”
“One area I felt wasn't fully captured is the challenge of sector transition knowledge gaps. Specifically, when IT leaders move from highly regulated environments like healthcare into education there's a significant adjustment period where existing frameworks don't map cleanly onto the new context. HIPAA expertise doesn't automatically translate to FERPA fluency and the governance structures are quite different. I would also add that vendor ecosystems for small public tech schools are underserved. Enterprise vendors build for large universities or K-12 districts. Institutions our size often fall through the cracks, getting solutions that are either overbuilt and overpriced or too limited to meet our needs.”
“we have an issue with middlee-management bottlenecks. Even when leadership is totaly on board and teams are actually open to trying new things, adoption can still kind of get stuck in the middle. A lot of middle managers are focused on short-term delivery and just keeping things running smoothly, so anything new can feel more like a risk than an opportunity. If the tool slows things down even a little at the start, it’s easy for them to fall back on what already works. And without really aligning incentives or giving them a sense of ownership in the change, they’re not super motivated to push it forward. That’s usually where adoption starts to plateau or lose signifcant momentum.”
“I think one of the most significant barriers not fully captures if the generational tech gap within the skilled trades. In a midsized construction firm, our most experienced field leaders- who I desperately need for quality and safety- are the most resistant to digital tools. The physical environment of a construction site (think extreme weather, dust, and the need for high durability tools and hardware) remains a very practical hurdle for many technologies that are designed for controlled office environments. Adoption isn't just a matter of will in construction, it becomes a matter of whether the tech can survive a February morning on a freezing, wet jobsite in Ohio.”
“I found this incredibly interesting as I work in the fintech SaaS space, where our goal is to get accounting and other types of firms to adopt technology. Evaluating this specific survey realizes that as an early company (less than 5 years old) we have a lot of work to do. Our largest barriers are that we do not have tech-minded leadership in a few key areas so priorities are not always focused on innovation and disrupts capabilities for us to streamline and adopt. We have a few key leaders - including myself - who know what and how to roll out processes and adopt technology but don't always have the talent to help us scale or think and drive along side us.”
What participants would have asked about
Responses that named additional barriers, sectors, or dynamics the structured items didn't cover. These directly inform v3 instrument design.
“I think that, in general, local non-profit organizations are faced with difficult decisions when it comes to implementing new technology. When choosing between investing in direct service or investing in new tech, direct service provision almost always wins. What's more, ability to invest in new tech depends on funding specifically designated (or specifically UNdesignated) to support this purpose. That's a rare and valuable commodity.”
“I think the biggest hurdle we have is our business has a legacy mindset, we have been in business 75 years and adaption to change, specifically AI, has caused most C-level and Director levels to circle the wagons around their own involvement and staff, due to fear of AI replacing the knowledge worker part of the business, since we are in manufacturing and 90% of our workforce are labor roles and not office staff.”
“The survey was thorough and thoughtful. We struggle with just getting into the current century when it comes to IT! We've attempted two major ERP conversions and both failed and (believe it or not) we are still running green screens for our core sales system. It's tough to get funding and support to really upgrade even though it's discussed all the time.”
“The only area I would add is the significant importance that effective communication that is tailored to the various stakeholder groups plays. I cannot overstate the value of communicating with each stakeholder group the information that is relevant to said group, along with progress reports tied back to return on investment.”
“Legacy leadership is much more resistant than newer, younger member of leadership. We have the capacity to do it, but as long as legacy leadership, CEO level, is hesitant, it never goes anywhere. Part of it is age, part of it is just general stubbornness, part of it is fear.”
“The rising cost was mentioned, but it has become a significant barrier. In the time I've been in the role, our budget has increased 10-fold due to software platforms and services the business units require, and it shows no sign of slowing.”
“For our organization, it consists of IT for many different uses - Regulatory, Legal, R&D, Manufacturing, and Service. Often a change made to optimize one use will negatively impact other uses. This is a huge barrier for us.”
“Besides the financial aspect, high turnover in leadership; every 2-3 years we have a new leader who wants to make their mark and will change a process that sometimes has not been fully implemented yet to something "better."”
“Our biggest challenge is in our new executive team and a lack of understanding of current systems and processes. They’ve engaged consultants who are incentivized only by cost savings not business optimization”
“We have experienced a major restructuring so I’m still impressed with how we are still implementing new technology! We lost about 25% of our workforce and are still gettigg by it done. Great survey.”
“I don’t know that this address the rapidly changing landscape, particularly in regards to AI. I think that even the most “prepared” companies are still not quite ready for full AI adoption.”
Critiques of the instrument itself
Where respondents pushed back on the survey design (scale gradations, specific phrasings). These are gifts; future iterations should address them.
“I think one of the biggest factors not mentioned here is organizational hierarchy or decision making. In terms of my organization, different functions are allowed a lot of autonomy to lead their teams the way they see fit. This distributed model leads to some wins within the specific vertical but often clashes with other vertices ability to take advantage of the scale of our business. It might be interesting to ask questions or understand how someone taking this survey would describe their organizational characteristics and decision making.”
Affirmations
Short positive feedback on the survey. Useful as engagement signal even though it doesn't change instrument design.
“Great questionset!”
“No, but thank you! :)”
“It's all covered, all clear”
How quotes were selected
Quotes were curated by the principal investigator from the full set of 162 open-ended responses. Pseudonymous IDs (P + first 6 of the Qualtrics response ID hash) replace any direct identifier. Verbatim quotes underwent a PII-risk scan (zero email/phone/URL/explicit-employer mentions detected) and a manual review for sector specificity before inclusion. Edited excerpts are flagged with edited=true.
The full set of 162 responses lives in the public dataset (the Q74_Feedback column of TABS_V2_CRP_2026_public_dataset.csv). Anyone can do their own thematic analysis from source.
Related
- Key Findings — the quantitative side of these themes
- Sample & Demographics — who these 162 voices belong to in aggregate
- ← Back to CRP 2026 Overview