Asana targets AI governance gap as UK IT costs spiral out of control
Shadow AI and poor governance are pushing UK organisations toward unplanned costs and compliance risk
The rapid spread of artificial intelligence (AI) tools across the UK workforce is generating a wave of unplanned costs and compliance failures that most organizations are struggling to contain.
Research published this week by Asana, a work management platform, found that 82% of UK information technology (IT) decision-makers have experienced unexpected or unplanned AI-related cost increases in the past 12 months. At the same time, 58% say their organization reports high AI adoption but limited measurable productivity gains.
“Most organizations are past asking whether their people will use AI. They already are. The challenge now is turning that into measurable business value, without losing the governance and visibility needed to manage risk,” said Christina Francis, head of UKI and Northern Europe at Asana.
The findings point to a deep accountability gap. More than six in 10 UK IT decision-makers say they are highly or fully accountable for AI-driven business outcomes, yet adoption is increasingly happening outside traditional governance processes. Those responsible for returns on AI investment are often unable to fully track or measure usage across their organizations.
A key driver of rising costs is the proliferation of shadow AI. One in four UK workers say they often use AI tools not formally approved by their organization, while 38% regularly use personal AI accounts for work tasks. Across the combined UK and US workforce, those figures rise to 32% and 45% respectively.
UK IT leaders estimate that almost a third of new AI tools introduced over the past year were adopted without formal review or approval. Rather than viewing shadow AI purely as a compliance issue, the research suggests it may signal that employees are seeking productivity gains their organizations have not yet enabled.
For business leaders, the challenge is not simply restricting AI use, but creating governed ways for employees to benefit from it.
“People want faster, smarter ways to work. The question is whether organizations can give them trusted, approved ways to do that, or whether they end up working around the tools entirely,” Francis said.
Governance failures and context
Saket Srivastava, chief information officer of Asana, and Francis met with UK-based journalists in London on June 2 to discuss AI governance and adoption, an event TechJournal.uk was invited to attend. The research, conducted by Censuswide among 1,002 IT decision-makers and 3,002 knowledge workers across the UK and United States, was published on June 12.
The governance shortfall is producing direct business harm. More than half of UK IT leaders (53%) say an AI tool or agent has taken an action in the past 12 months that resulted in financial, legal, reputational or compliance damage. Nearly half of UK workers (49%) say they do not know how their company uses their work, including emails, documents and tasks, to train or improve AI systems.
Execution failures are compounding the problem. Nearly half of UK IT leaders (46%) say AI initiatives often or always fail or stall because AI lacks complete organizational context. Some 37% of UK knowledge workers spend at least 30 minutes a day fixing or reworking AI outputs due to missing context, while 67% say they have to re-explain context to AI tools at least sometimes.
Workers are also struggling to feed AI the information it needs. Two in five UK employees say they need to check three or more tools to gather the context required to complete their work. The cumulative cost of that friction is significant.
Time lost to reworking flawed outputs, re-explaining background information and switching between disconnected systems adds up to a considerable daily productivity burden. Many organizations have yet to solve the challenge of providing AI with the structure and knowledge needed to deliver reliable outcomes at scale.
“As organizations move toward more dynamic, cross-system workflows, the need is shifting from coordination to Adaptive Work Orchestration, where humans and AI operate against shared context, with embedded governance and continuous visibility,” said Riana Barnard, industry analyst at Frost & Sullivan.
Francis said the organizations that get ahead will be those that combine visibility, governance and context, treating them not as competing priorities but as a single integrated challenge.
Asana’s agentic response
On June 4, Asana used its Work Innovation Summit in London to unveil what it calls an operating system for human-agent teams. The new product suite, called Agentic Work Management, is designed to enable organizations to run critical workflows in which humans and AI agents work from the same plan, with shared context and unified governance.
Asana refers to the approach as Adaptive Work Orchestration, an AI-powered operating system designed to bridge the gap between human teams and AI agents, enabling them to execute critical business plans together. The company also uses the term "Agentic Work Management" to refer to the same platform.
“For 18 years, Asana has solved one of the hardest problems in business: helping teams coordinate at scale across goals, decisions and handoffs. The foundation we built is precisely what the agentic era requires,” said Dan Rogers, chief executive of Asana.
Central to the launch is Asana Dash, an AI chief of staff for individual users that captures follow-ups from meetings, Slack threads and email and converts them into structured work items. AI Teammates, the platform’s agent layer, now feature a chat-based interface, a skills library for repeatable work, and integrations with tools including Gmail, Outlook, Slack, HubSpot, Figma and Canva.
Early results from enterprise deployments point to significant operational gains. FedEx, the logistics company, deployed AI Teammates across its marketing and sales operations, consolidating intake from more than 24 forms into a single intelligent workflow. Planning cycles fell from weeks to days, and more than 1,200 hours were reclaimed annually.
The deployment generated hundreds of thousands of dollars in operational savings. At the leadership level, AI Teammates provided full visibility into global initiatives, reclaiming over 300 hours that had previously been spent on manual alignment. In the sales function, intake review time dropped from 90 minutes to 30 minutes.
Three new applications are due to follow: Asana Service Management for IT and HR teams, Command by Asana for product and engineering workflows, and Asana Client Management for agencies. All three build on Asana’s acquisition of StackAI in May 2026, which extended its orchestration capabilities across enterprise systems including customer relationship management and enterprise resource planning platforms.
Agentic Work Management and AI Teammates are available immediately. Asana Dash and the three new applications will be released in phases over the coming months.