Dawn’s GenAI Adoption Study of 40 billion-dollar revenue enterprises finds GenAI moving from proof-of-concept to production: 78% of companies are formally deploying it today, and a majority expect the technology embedded in every routine task by 2027.

Momentum is accelerating. More than half of respondents aim for enterprise-wide rollout within 6 months, and executives rate GenAI a top-three agenda item for both internal productivity (weighted score of 8.0/10) and external products (weighted score of 7.6/10). These firms view GenAI as the lever to compress cycle times, cut cost, and boost revenue simultaneously – ambition that underpins the rapid expansion of pilots into core workflows.

Usage breadth and early economics are compelling. Over 70% already run ten or more GenAI initiatives, spanning workflow automation, knowledge ops, sales enablement, and customer support. While half of “fastest” projects still take 8+ weeks from idea to production, the balance of ROI is net-positive (+25 pp) and tilts first toward cost reduction and productivity gains, with revenue growth close behind. Budgets are following the momentum: 43% now ring-fence dedicated GenAI funding, and nearly half allocate 2-5% of total IT spend to these projects.

Scaling remains messy. Security dominates anxieties – rated 6.3/10 on average as the most predominant business concern – with application-level security the single largest technical barrier (9.4/10 on average). Talent shortages, data quality gaps, and regulatory friction follow. Tooling is fragmented: a majority juggle 4+ LLMs and 4+ GenAI tools, even as OpenAI soaks up c. 60% of spend. This patchwork amplifies governance complexity and inflates integration effort.

Governance is racing to catch up. 63% now have a formal AI policy, typically owned by the CTO or engineering lead, and every firm monitors shadow-AI usage to curb risk. Firms cite easy-to-use, secure tools, workforce training, and clearer regulation as the top enablers for scale. Only 23% have cancelled GenAI projects, underscoring durable conviction despite hurdles.

In all, the findings paint a world in transition. Enterprises that pair bold deployment with disciplined security, unified tooling, and upskilled talent will widen the productivity gap; laggards risk obsolescence as GenAI-first efficiency becomes table stakes.

We hope you enjoy reading the findings as much as we did.

Geographical mix

75% of respondents were in the US, and 25% in Europe.

Roles

We surveyed enterprise leaders across strategic and technical functions.

Type of enterprise

We recruited leaders from the “early adopting” enterprise verticals – financial services, telcos, and software service providers. All had >$1b in revenue, 60% were >$10b.

Adoption

>75% of respondents are formally deploying GenAI, beyond experimentation and pilots

Q: Where is your company today on its GenAI‐adoption journey?

Timings

Over half of companies plan to have deployed GenAI enterprise-wide in next six months.

Q: If your company is not deploying GenAI enterprise-wide, when do you expect to reach that stage?

2027 Vision

A majority of respondents expect GenAI to be in every routine task and daily workflow in next two years.

Q: In a few sentences, what do you want GenAI to change in your business by the end of 2027?

Score 0-10 of priority

While both internal and external GenAI initiatives are seen as priorities, enterprises are more focused on embedding GenAI into internal operations. Only 7 out of 40 respondents rated internal use cases ≤6 in priority, compared to 14 for external.

Q: On a scale of 0 to 10, how much of a priority is embedding GenAI into your internal operating systems (e.g., productivity tools, workflows)?

KPIs

Most enterprises want to reduce headcount, eliminate repetitive tasks, and improve their product.

Q: Which KPIs would you most like to see improved through the use of GenAI?

# initiatives

Over 70% of enterprises report having >10 GenAI initiatives underway.

Q: How many individual GenAI initiatives are currently in proof-of-concept or production at your company?

Initiative allocation

The types of initiatives being implemented vary, with agents now a plurality.

Q: Roughly what percentage of your GenAI-related time or effort is allocated across the following initiatives (%)

Time to value

Over half of respondents reported their fastest GenAI initiative taking longer than 8 weeks from idea to production.

Q: How many weeks did your fastest GenAI initiative take to go from initial idea to first production use?

Automation ambitions

Ambitions span from fully automating customer-facing and compliance tasks to augmenting employee productivity in sales, development, and knowledge work.

Q: If you could automate just a handful of problems with GenAI, what would they be?

Top initiatives

Enterprises are dedicating a greater % of their budgets to workflow automation projects, beyond chatbots and knowledge management.

Q: Please detail the top three GenAI initiatives by investment

Allocation

Software engineering and customer support are the two largest recipients of GenAI investment, but all departments have meaningful representation.

Q: How are you allocating GenAI investment across departments?

Examples

Over 70% of enterprises report having >10 GenAI initiatives underway.

Q: For the top three GenAI initiatives by investment, please provide the following details for each

ROI today

On balance, the ROI is considered to be positive across the sample (+25pp). Most companies that do not yet see ROI are positive that it will realised in the near future.

Q: How would you categorise the return on investment (ROI) on your GenAI initiatives in production today?

KPIs today

GenAI is most affecting costs today, with employee productivity and revenue growth secondarily.

Q: Which KPIs does your GenAI ROI most closely align to?

Business concerns

Security is the dominant concern when deploying GenAI, far outweighing other factors. A shortage of skilled staff is the second most cited challenge. Despite large AI budgets (see ‘AI Procurement’), proving ROI and managing costs remain major anxieties.

Q: Please rank your top three business concerns about GenAI

Score 0-10 of barriers

App security is also the largest technical barrier to implementing GenAI application. Additional critical blockers involve lack of talent and poor data quality. Regulation is the largest external blocker.

Q: On a scale of 0-10, what are the main barriers in productising GenAI applications in your organisation? (0 being not a barrier at all; 10 being barrier preventing progress)

Score 0-10 of capabilities

Many governance capabilities that they rate as urgent have not been put into production today.

Q: On a scale of 0-10, how important are the following capabilities for orchestrating GenAI usage at scale in your company? (0 being not at all important; 10 being absolutely critical). Which of these capabilities do you currently have in place today?

# models

>50% have >4 models.

Q: How many large language models (LLMs) does your company currently use in production?

Largest provider

OpenAI is the largest provider for more than half surveyed…

Q: Who is your single largest LLM provider?

Larger provider spend

… representing >60% of total mean spend.

Q: Approximately what percentage of your overall GenAI usage or spend does this provider represent?

# tools

>55% have >4 tools.

Q: How many separate tools do you use to “manage” GenAI?

Top tools

Enterprise GenAI budgets are fragmented: while OpenAI leads, significant spend still funnels to specialist platforms like UiPath for automation, Salesforce for CX, and Anthropic for safe language models.

Q: Please list out the top five tools by spend

Statements

They are open to a new, dedicated GenAI tool, and concerned about data quality. They need a platform that is enterprise-wide, secure, and cost-effective.

Q: To what extent do you agree or disagree with the following statements in reference to GenAI applications and initiatives in your organisation?

Cancelled initiatives

Only a minority (23%) have cancelled a GenAI project.

Q: Have you shelved or cancelled GenAI project(s) in the past 12 months?

Data in cloud

Half would not even consider putting data into a public-cloud tool.

Q: Would you be willing to place sensitive data into a secure public-cloud GenAI tool today?

Shadow IT

All have some form of shadow IT monitoring.

Q: How does your company currently monitor and manage unsanctioned (“shadow”) AI tool usage by employees outside official policy?

Changes to scale GenAI

Easy-to-use tools and sensitive data protections came up often as an important enabler for adoption.

# Times Mentioned in Top 3 (N=40)

Q: What changes or enablers would help your company scale GenAI adoption more effectively?

Formal AI memo

>60% have a formal AI policy.

Q: Does your company have a formal, written AI policy or strategy?

Exec accountability

A majority held the CTO or engineering leadership accountable.

Q: Which executive role is formally accountable for enforcing your company’s AI policy or strategy?

GenAI acumen

Half of the respondents self-reported themselves as “intermediate” acumen – understanding the basics, with only 3% self-reporting as “advanced”.

Q: How would you describe the current level of GenAI acumen across your C-suite?

Human-in-the-loop approvals

External AI was the most prominent example of needing a human-in-the-loop.

Q: For which types of GenAI processes/ applications, do you formally need a human-in-the-loop?

No human-in-the-loop approvals

Internal tools were more flexible.

Q: For which types of GenAI processes/ applications, do you not formally need a human-in-the-loop?

Model re-evaluation

75% planned to re-evaluated models at least every quarter.

Q: How frequently do you re-evaluate/plan to re-evaluate models deployed in production?

Exec GenAI discussion

Most exec teams discussed GenAI every quarter.

Q: How often do you discuss GenAI within the exec team?

Speed vs control

Most organisations prefer to move more slowly over sacrificing control.

Q: Where would you place your organization on the speed vs. control spectrum for GenAI deployment?

Dedicated budget

Over half of respondents had a dedicated GenAI budget. Over 4 in 5 respondents allocate more than 2% of their annual IT budget.

Q: Do you have a dedicated budget for GenAI initiatives?

GenAI as % of IT

Almost half allocated 2-5% of the IT budget to GenAI projects.

Q: What percentage of your total IT budget is currently allocated to GenAI projects (including relevant cloud compute costs)?

Budget cycle

Most didn’t have a different budgeting cycle.

Q: Are GenAI projects managed on a different budgeting or planning cycle from other IT or innovation projects?

Centralised vs decentralised

Most budgets are managed centrally.

Q: What proportion of the budget is managed centrally (e.g., by the CIO/CFO) vs decentrally (e.g., by individual business unit leaders)?

Max spend before sign-off needed

Around half of enterprises can green-light GenAI projects exceeding $50k without procurement sign-off.

Q: What is the maximum spend that does not require formal procurement sign-off for a GenAI-related project? (USD)

Budget approver

The majority of final approvals sit with the commercial side of the business.

Q: Who typically needs to approve a GenAI project?

Additional steps

Most don’t require any additional steps for GenAI projects.

Q: Are there additional procurement steps for GenAI?

Dawn Capital LLP is a limited liability partnership incorporated in England & Wales (with registered number OC321845) and is authorised and regulated by the Financial Conduct Authority.

This report contains highly confidential and proprietary information about Dawn Capital LLP, its business and personnel. As a result, this report is provided on a confidential basis. By accepting this document, you agree that you will not use any of the information contained therein, including that regarding the business, operations, financial condition, or trade secrets of any of the investment partnerships managed or advised by Dawn Capital LLP (the “Funds”) and/or their respective portfolio companies, except with respect to your participation as an investor in said Funds.

This report is provided for information and discussion purposes only and does not purport to be comprehensive. No representation is made, or assurance given, that the statements, projections or forecasts are correct or that the objectives of the Funds and/or the portfolio companies will be achieved. No representation, warranty, express or implied, is given by any person as to the accuracy or completeness of the information and opinions contained herein and no responsibility or liability is accepted for the accuracy or sufficiency of any of the information or opinions, for any errors, omissions or misstatements or for any other communication, written or otherwise, in connection with the Funds and/or the portfolio companies. No information in this report will form the basis of any contract or an inducement to enter into any contract.

Accordingly, to the maximum extent permitted by law, neither Dawn Capital LLP nor the Funds and/or the portfolio companies nor any of their respective officers, employees, members or affiliates shall be liable for any direct, indirect or consequential loss or damage suffered by any person as a result of relying on any information or opinions contained herein or in any other communication in connection with the Funds and/or the portfolio companies. Accordingly, no reliance whatsoever should be placed on this report or its contents.

NO PERSON MAY DISCLOSE OR REPRODUCE ANY PORTION OF THIS REPORT WITHOUT THE PRIOR WRITTEN CONSENT OF DAWN CAPITAL LLP.