How skilled is the AI workforce according to tech executives?
Tech executives in the UK are expressing strong confidence in their workforce’s AI capabilities. A survey by Zartis reveals that 85% of these executives rate their teams’ combined AI knowledge and expertise as ‘skilled’, reflecting a strong foundation in AI across organizational levels.
Over half (51%) of these executives go a step further, labeling their workforce as ‘highly skilled’—indicating that a large portion of tech professionals have advanced AI competencies, positioning their companies well for leveraging AI technologies.
Nearly every tech company is embracing AI
AI adoption among UK tech companies is nearly universal. According to the same Zartis study, 94% of executives report that their organizations use AI in some capacity. Widespread implementation has highlighted AI’s integral role in current tech operations.
The remaining 6% of companies are actively exploring or researching AI, indicating an impending full adoption. Worth noting, not a single respondent claims to be completely avoiding AI, pointing out the technology’s pervasive influence and acceptance in the industry.
Industry momentum driving AI investment decisions
Industry pressure greatly influences AI investment priorities, with 40% of tech executives feeling compelled to prioritize AI investments due to the momentum surrounding this technology.
The competitive nature of the industry is driving this urgency, as companies recognize the potential drawbacks of lagging behind in AI adoption. This pressure is now propelling investment decisions, reinforcing the strategic importance of AI in keeping a competitive edge.
What’s stopping full AI adoption in tech?
Top financial and technical hurdles in AI adoption
Despite the recent enthusiasm for AI, several financial and technical challenges limit its full adoption. Budget restrictions are a major barrier here, with a surprising 41% of executives citing it as their primary obstacle.
High costs associated with AI development and deployment strain financial resources, making it difficult for some companies to scale their AI initiatives.
Adding to this, a shortage of AI talent, mentioned by 38% of executives, further limits this progress. Demand for skilled AI professionals has outstripped supply, creating a bottleneck for many organizations.
Why integration and security are AI’s biggest challenges
Technical complexity adds another layer of difficulty, with 35% of executives acknowledging it as a challenge. Integrating AI with existing systems is a complex task requiring specialized skills and knowledge.
Integration challenges are also being cited by 44% of executives, pointing out the difficulties in merging new AI technologies with legacy systems. Concerns over cost and ROI uncertainty, noted by 42% of respondents, add more complexity into adoption decisions. Executives are grappling with justifying the initial investment amid unclear returns.
To top this all off, data privacy and IP security issues, addressed by 38% of executives, also pose serious risks, requiring strict and careful measures to protect sensitive information.
Michal Szymczak on the irony of AI confidence vs. barriers
Michal Szymczak, Head of AI Strategy at Zartis, commented on the paradoxical nature of AI adoption. Despite executives’ strong confidence in their AI capabilities, they have simultaneously acknowledged several barriers.
Szymczak points out that AI adoption is not a straightforward process, and is one that requires major financial investments.
Companies face complex challenges, including data privacy concerns and the integration of AI with existing technology stacks—highlighting the irony in executives’ attitudes—as they boast about their AI expertise while admitting the major hurdles that still limit meaningful progress.
Balancing ROI concerns with efficiency gains in AI
AI adoption comes with both excellent opportunities and serious concerns, particularly for return on investment (ROI) and efficiency.
For 42% of tech executives, ROI uncertainty is the primary concern—stemming from the high initial costs and the unpredictable nature of returns, making it challenging to justify the expenditure. Executives must consider both the immediate financial outlay and the long-term implications of AI investments, including maintenance and future upgrades.
On the other hand, 53% of executives recognize cost savings through improved efficiency as a measurable long-term benefit of AI adoption. AI can streamline operations, reduce manual processes, and improve decision-making, leading to greater cost reductions over time.
For example, AI-powered automation in manufacturing can improve production efficiency and lower labor costs, while AI-driven analytics can optimize supply chain management and minimize waste. These ultimately contribute to a more solid bottom line, even if the initial ROI is unclear and difficult to forecast.
How much are companies investing in AI?
Investment in AI is large and growing among UK tech companies, pointing to the technology’s perceived importance and potential benefits. In 2024, 93% of companies report spending at least £100,000 on AI initiatives—indicating a broad commitment to integrating AI into many different aspects of business operations.
Adding to this, 44% of these companies have allocated £500,000 or more to AI projects, showcasing a relatively broad willingness to invest heavily in this tech despite potential financial risks.
Where is AI investment going? Top focus areas
Spotlight on AI investment priorities
Tech companies are channeling their AI investments into specific areas where they expect to see the most impact. Software development is seen as the most popular area for AI investment, with 59% of companies focusing their resources here.
AI tools can accelerate development cycles, improve code quality, and reduce time to market, offering tangible competitive advantages.
Quality assurance is another key focus area, with 44% of companies investing in AI to support testing processes, identify defects early, and develop higher software quality. Similarly, 44% of these companies are prioritizing DevOps and automation, leveraging AI to streamline workflows, improve deployment pipelines, and boost overall operational efficiency.
Growing investments here have pointed out a broad drive for adopting a strategic approach to maximizing the benefits of AI across different facets of software development and operations.
Angel Benito’s take on AI investment trends
Angel Benito, CTO at Zartis, noted that organizations now feel pressured to keep pace with AI developments, driven by the fear of falling behind competitors—motivating companies to invest in AI despite uncertainties about ROI.
Benito also emphasized that the potential for long-term cost savings is a major driving force behind these investments. That said, he still cautions that successful AI adoption requires a well-curated implementation plan that focuses both on acquiring the right tools and on developing the required skills and crafting a culture of innovation.
According to Benito, the human element is just as important as the technology itself in realizing the full potential of AI.
The must-have AI applications for developers
AI is disrupting software development with tools that improve many different stages of the development lifecycle. AI-powered copilot tools for coding, used by 53% of companies, assist developers by suggesting code snippets, detecting errors, and automating routine tasks—reducing development time and improving code quality when well implemented.
Improved continuous integration and deployment (CI/CD) processes, cited by 52% of executives, is another powerful application of AI—improving CI/CD pipelines with automated testing, early issue detection, and smoother deployments. This ultimately then leads to more reliable software releases and faster iteration cycles.
Higher quality and focused team communication and collaboration tools, favored by 46% of companies, leverage AI to streamline workflows, facilitate knowledge sharing, and improve project management. Such tools are helping teams work more effectively, reducing the time spent on coordination and therefore increasing overall productivity.
Tech leaders support stricter AI regulations for better outcomes
The regulatory environment for AI is evolving with growing momentum, with many tech executives advocating for increased government oversight. Over three-quarters of UK tech executives favor more stringent regulations, anticipating that frameworks like the EU AI Act will provide clearer guidelines and standards for AI deployment.
These regulations are expected to address priority issues such as data privacy, ethical AI use, and transparency, which are all key for building trust and guiding responsible AI implementation. Executives confidently believe that well-crafted regulations can limit risks and create a more predictable environment for AI innovation.
The road ahead
Are you investing strategically in AI to keep pace with competitors and truly transform your operations and drive long-term growth? Leaders must carefully consider how overcoming the barriers of budget constraints, talent shortages, and integration challenges can position your brand as a leader in innovation.
