31% No
69% Yes
My organisation is delaying important investment decisions due to an expected increase in regulation
27% No
73% Yes
Inconsistent and fragmented AI regulation will have a major impact on my organisation and our growth strategy
The global AI regulation landscape is rapidly evolving. This uncertainty is having an impact on AI investment levels.
AI regulation is causing concern Top business impacts identified
Regulatory uncertainty needn’t cause delay
To gain traction, businesses need to develop an AI governance structure that anticipates AI risks specific to their business in addition to evolving legal requirements and regulatory approaches.
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Business leaders of large international organisations shared their views with us on the importance of AI Traction. This included General Counsel and C-suite executives with responsibility for strategy and operations.
450
of business leaders anticipate that in 3 years time 11-20% of their revenue will be directly attributed to AI
52%
of business leaders believe that AI is now an important mechanism for protecting their organisation’s revenue and bottom line
74%
of business leaders believe that organisations which fail to embrace AI-driven change are increasingly unviable
65%
Despite business leaders firmly believing that AI will transform their business, 63% do not currently have a formalised AI roadmap in place and appear to lack a roadmap for long-term, high-impact adoption.
The inactivity risk
Laws of AI Traction Charting a course from ambition to action
Download the full report
There is a significant gap between the ambition of large businesses to leverage AI solutions and their progress towards AI adoption. Laws of AI Traction explores this gap and how to bridge the divide.
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Applying structure to uncertainty
Corporate agility Workforce transformation Digital resilience and data management
Dimensions of AI traction
Home
450 business leaders and General Counsel across the UK, Ireland, Kingdom of Saudi Arabia, and UAE shared their views on AI.
Business leaders predict significant gains from AI, but are delaying investment decisions.
A chief concern is the ambiguity trap created by changing and fragmented laws and regulations.
Although confidence in achieving long-term returns is high, uncertainty creates inactivity risk.
Establishing a comprehensive AI governance framework is crucial to overcome this paralysis.
At a glance
Despite the AI hype, many leadership teams aren't at the stage of fully understanding where the technology can transform business teams or services and product, and executing on targeted strategic development.
Simon Elliott Head of UK, Ireland and Middle East Privacy, Cyber and AI Team
Hear more about the strategic context for this report from Rowena Rix, Head of Innovation and AI, UK, Ireland and Middle East
Internal and external security issues are already creating significant operational costs for organisations. AI is multiplying cyber threats. With organisations implementing AI in such a rapid and diffuse way, a robust data strategy and strong data governance processes to implement AI effectively and safely is critical.
The Gartner Data Governance Maturity Model, also known as the Gartner Enterprise Information Management (EIM) Maturity Model, provides a framework for organizations to assess and improve their data governance practices.
1
Reactive Data quality processes are reactive. Policies have been created, but adoption is low. Aware There is an awareness surrounding the need for standardised data policies and processes, but no clear ownership. Unaware There is no data governance, data ownership or accountability in place.
Proactive There is company-wide compliance with governance protocols. Data stewards and owners are identified and active.
Effective Utilising data and managing information is seen to provide a competitive advantage. The team responsible for data management is well established and active. Managed Data policies have been developed, initiated and are well understood. Data metrics are well defined and accessible.
Hover over the graph to find out more about the stages of maturtiy.
51%
Reactive, aware or unaware
27%
Procative
22%
Effective or managed
Gartner Data Governance Maturity Model 1 Most organisations fall in the bottom two-thirds
Antonis Patrikios Partnaer, Co-lead Global Privacy & Cyber Group, Global TMT Sector Lead
$29.7m average operational costs to businesses of internal and external security issues
Implementing sufficiently scalable digital infrastructure and sound data governance for rapid and safe transformation, and a robust data strategy.
Digital resilience and data management
Companies need to manage potential legal risks if they are reducing headcount and must carefully consider employment law implications across different jurisdictions as they innovate and implement new technologies.
42% Augmenting the workforce and boosting growth through productivity gains
58% Reducing overall headcount and costs
Corporate workforce transformation AI intentions Dial leaning towards reducing headcount
of organisations say that workforce productivity has Improved since their organisatlon has adopted Al tools
75%
of organisations predict that by 2038 Al will generate more revenue than human employees
Sarah Beeby People, Reward and Mobility Partner, Co-Clients and Markets Partner
Preparing the workforce for the changes wrought by AI.
Workforce transformation
48%
Seek to license
41%
Buy third-party AI solutions as a service
33%
Take a minority stake in an AI organisation
32%
Build AI solutions/tools internally
Top 4 alternative approaches to M&A to enhance AI capability
of business leaders will use M&A to enhance their company’s AI capabilities over the next three years.
70%
When the landscape is changing so rapidly, businesses need to make difficult decisions fast. Do they acquire capabilities through corporate transactions, develop proprietary products, or buy off-the-shelf solutions? Or do they forge a strategic partnership? A sophisticated strategy might target all these approaches at different times and for different reasons.
Building strategic and operational capacity to quickly adapt and respond to the opportunities offered by AI.
Corporate Agility
Implementing sufficiently scalable digital infrastructure and sound data governance for rapid and safe transformation, and a robust data strategy
Preparing the workforce for the changes wrought by AI
Building strategic and operational capacity to quickly adapt and respond to the opportunities offered by AI
Corporate agility
Our study has helped identify three key dimensions needed for businesses to effectively implement AI into their organisation and bridge the gap between AI ambition and AI action. Planning for each of the three areas is a challenge of both strategy and delivery. Success will not only smooth the adoption of AI but also ensure that it delivers maximum business value.
Previous
The moment to size AI opportunities is now The inactivity risk Regulatory uncertainty needn't cause delay
Organisations need to ensure that they're not waiting to see what others do, and suddenly introducing AI without understanding the implications.
Good resilience, cybersecurity and data management governance controls are a core part of a broader AI governance framework that is aligned with emerging good AI governance practice.
M&A and strategic investment is a tried a tested route to building capabilities in a new area or sector, and the AI revolution is no different.
Joe Collingwood Corporate Partner
Listen to Joe Collingwood, Corporate Partner discuss corporate agility
Sarah Beeby, People, Reward and Mobility Partner, Co-Clients and Markets Partner shares her view on workforce transformation
Simon Elliott, Partner, Head of Privacy, Cyber and AI Team UK, Ireland and Middle East and Antonis Patrikios, Partner, Co-lead Global Privacy & Cyber Group, Global TMT Sector Lead share their perspectives on digital resilience and data management
The need to have an AI strategy and a considered AI roadmap coupled with an AI governance strategy is clear and present. Organisations that find ways to leverage AI strategically while proactively managing the associated risks are the most likely to enjoy success.
Explore our AI Global Solutions Hub here
Explore the 12 components for an effective AI governance framework
of business leaders think that the General Counsel/ legal team’s role in AI strategy is instrumental in ensuring positive business performance
of organisations are not involving their legal team from the outset
44%
The strategic opportunity for in-house legal teams
Before GDPR, we had a good idea as to the regulatory framework that was coming. Businesses did not stop processing data for fear of getting it wrong; it meant being thoughtful, deliberate and responsible in approach. Although arguably more complex, the same could be said for AI deployment.
Rowena Rix Head of Innovation and AI, UK, Ireland and Middle East
