A recent study commissioned by Hewlett Packard Enterprise (HPE) reveals that while 96% of UK and Ireland businesses have established AI objectives, only a third believe they are well-equipped to reap the benefits of AI. Critical gaps including low data maturity, ineffective networking, and overlooked ethical and compliance considerations are hindering successful AI implementation. Despite businesses planning to increase AI budgets, the lack of a holistic approach and understanding of AI technology could potentially affect future return on investment. The report also highlights the business risk of overconfidence in AI without proper ethics and compliance.
- One third of IT leaders in the UK&I believe their organisations are fully set up to realise the benefits of AI.
- Organisations are overlooking key areas critical for successful AI outcomes, such as low data maturity levels, deficiencies in networking and compute provisioning, and ethics and compliance considerations.
- Businesses risk negative impacts from AI, including exposure of proprietary data, decreased ROI due to ineffective models, and increased carbon emissions from high power demands if they don’t adopt a comprehensive end-to-end approach to AI implementation.
UK and Ireland Businesses Embrace AI, Yet Stumble on Delivery
In a landscape where artificial intelligence (AI) is quickly becoming a business imperative, a recent report reveals a somewhat disconcerting truth. Despite a staggering 96% of UK and Ireland organisations having set or already pursuing AI goals, only a mere third believe they are fully equipped to harness the benefits of AI.
AI Adoption: More Than Just a Buzzword
The research, commissioned by Hewlett Packard Enterprise and aptly titled ‘Architect an AI Advantage’, surveyed almost 400 IT leaders across the UK and Ireland. It found that while there is a clear commitment to AI, with 94% of businesses planning to increase their budgets, there are gaps in strategy and understanding that could seriously hamper future returns.
Matt Armstrong-Barnes, chief technologist for AI at Hewlett Packard Enterprise, expressed his concern saying,
“Businesses are investing in AI without first taking a holistic view of the technology and how to implement it. Diving in before considering whether they are set up to benefit from AI and who needs to be involved in its roll-out will lead to misalignment between departments and fragmentation that limits its potential.”
The Data Dilemma: Quality Over Quantity
Quality data is the lifeblood of effective AI, yet the research shows low levels of data maturity. A scant 6% of organisations can perform real-time data operations, and fewer than 6 in 10 businesses are fully able to handle key stages of data preparation for AI models. This could slow down AI creation and lead to inaccurate insights and negative return on investment.
Compute and Networking Challenges
The end-to-end lifecycle of AI also presents unique demands on compute and networking infrastructure. While a majority of IT leaders express confidence in their network and compute capacity to support AI, less than half fully understand the unique demands of the AI workloads. This could lead to inaccuracies in resource provisioning.
The Ethics and Compliance Conundrum
Surprisingly, the report reveals that ethics and compliance, despite being critical considerations in AI, are being largely overlooked. Legal compliance and ethics were deemed least critical for AI success by IT leaders. This, coupled with a lack of involvement of legal teams in AI strategy, poses a significant risk.
Final Thoughts
The report paints a clear picture: the rush to embrace AI is palpable, but the approach is fragmented. As businesses move rapidly to understand and implement AI, they risk stumbling over data readiness, strategy, security, and governance. This could lead to ineffective models, potential legal battles and a negative impact on brand reputation.
As Armstrong-Barnes rightly points out, businesses need to adopt a more comprehensive end-to-end approach to AI. Only then can they truly harness the transformative power of this technology and secure the long-term success they so clearly desire.
FAQ
Q: In relation to HPE’s commissioned research, what percentage of UK and Ireland businesses have or are setting AI goals?
A: 96% of UK and Ireland businesses have started or completed setting up AI goals.
Q: In relation to HPE’s commissioned research, what percentage of IT leaders believe their organisations are fully set up to realise the benefits of AI?
A: Only one third (32%) of IT leaders believe their organisations are fully set up to realise the benefits of AI.
Q: What are some key areas where businesses are overlooking that impact their ability to deliver successful AI outcomes?
A: Businesses are overlooking low data maturity levels, deficiencies in networking and compute provisioning, and ethics and compliance considerations.
Q: How many organisations can run real-time data pushes/pulls to enable innovation and external data monetisation?
A: Only a small percentage (6%) of organisations can run real-time data pushes/pulls to enable innovation and external data monetisation.
Q: What percentage of IT leaders believe their network infrastructure is set up to support AI traffic?
A: 92% of IT leaders believe their network infrastructure is set up to support AI traffic.
Q: How many IT leaders admitted to having a full understanding of the demands of various AI workloads across data acquisition, model training and monitoring?
A: Less than half of IT leaders admitted to having a full understanding of the demands of various AI workloads.
Q: How many organisations are not involving legal teams in their business’s AI strategy conversations?
A: Almost 1 in 4 organisations (20%) are not involving legal teams in their business’s AI strategy conversations.
Q: What are some potential risks for businesses that lack an AI ethics policy?
A: Businesses risk exposing their proprietary data, developing models that lack compliance and diversity standards, and facing negative impacts to their brand, loss in sales, or costly fines and legal battles.
Q: How many IT leaders admitted to having a lack of full understanding of the IT infrastructure demands across the AI lifecycle?
A: Less than half of IT leaders admitted to having a lack of full understanding of the IT infrastructure demands across the AI lifecycle.
Q: How can businesses improve their AI approach to avoid negatively impacting their long-term success?
A: Businesses must adopt a comprehensive end-to-end approach across the full AI lifecycle to streamline interoperability, identify risks and opportunities, and lay the groundwork for their deployments.
