Business leaders in 2024 are all excited by the opportunities from artificial intelligence (AI), whether they intend to use it or not. The direct benefits are clear and, particularly in the recent economic climate where business resilience and the bottom line are top of mind.
As it stands, most organizations do appear to have big plans for AI. 86% of senior business leaders globally have already deployed AI tools to enhance existing revenue streams or create new ones, according to our recent AI survey of over 1,272 businesses. And in the UK, 92% have AI implementations planned, in process or already completed. But the level of innovation seems to be a sticking point for businesses when incorporating AI into their business plans.
69% of business leaders stated that they are more focused on using AI to spur innovation and increase revenue than on productivity improvement and cost optimization. However in practice this is simply not the case. Just 4% of businesses are currently leveraging AI as a differentiating element that is transforming their business. Meaning, there is a big gap between intention and implementation when it comes to innovating with AI. So, why are businesses facing challenges?
Head of Innovation, Tata Consultancy Services (TCS).
Aversion To Risks
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Many businesses struggle with innovation because of a shortage of robust financial models for digital transformation a lack of leadership support, a culture that encourages innovation and structures being in place, missing workforce skills, and concern from business leaders about regulatory issues. However, beyond these hurdles, when it comes to innovating with AI, risk aversion is often the major roadblock for business leaders. Only 23% of businesses in the UK have reported wanting to experiment and take risks with AI to maximize its benefits.
Any innovation involves trying new things, but with AI, there are multiple types of risks. Firstly, the technology is evolving extremely rapidly – which means the risk of obsolescence is high, and skills can be hard to acquire. The proliferation of platforms and tools can also create a risk of suboptimal choice making. Because there are so many options for business leaders to choose from, it can be hard to know which is right for your organization.
The cost behavior of AI applications at scale is not well understood, which creates commercial risks for businesses to grapple with too. And with governments still struggling to create and rewrite regulation for emerging AI technologies, there is the specter of regulatory and compliance risks. Companies might be on the hook for a lack of explainability or transparency while using AI, which in turn creates possible brand impact.
These risks are intimidating because AI technology is new, and the learning curve can be steep for many leaders. Nevertheless, issues can be mitigated. With a mature innovation approach, experimentation, test-and-learn methods, and governance models, organizations can build safe environments to use and innovate with AI. If it is complex or tough to implement these measures alone, turning to the right partners is also a popular option to build confidence with using AI to generate improve processes and create new streams of income.
The Complexity of AI
AI requires more data than traditional business software to be effective, as it needs to be trained on large quantities of high-quality data which can be challenging to obtain. Additionally, algorithms are often quite complex and require specialists to maintain and develop, and legacy technology may need to be updated to support software. This is large-scale change for leaders to manage, if they want to actually be innovation-first and AI-enabled. It can also be costly.
Some leaders might baulk at the cost without being able to visualize data, results, and potential reward or may simply not feel comfortable selling the costs to internal stakeholders. An additional worry for businesses is the changing capabilities of the tools themselves. AI is evolving quickly, and the best model for the task at hand one week may not be the best the following week. Having an orchestration layer that can move applications between providers without impacting the business, is therefore critical for building agility into AI business offerings and processes. However, with AI being a newly prevalent technology with an abundance of information about it published daily, not all businesses will be aware that offerings for this exist yet.
Innovating in a safe environment
Many of these challenges will be addressed by enterprises with time, however, for those visualizing getting ahead of their competition now and struggling to do so in practice, it’s essential to have a safe environment to ‘test’ in. Whether this be having the right employees in place with the skills to bounce ideas from, or with the experience to advise on these new technologies already, or even to bring in an expert IT services partner who can offer stakeholders a safe environment to innovate and to implement effective change.
AI might be a widespread phenomenon, and small-scale implementations are certainly happening amongst UK businesses. However, it is clear that without further support and expertise, many enterprises will not be making the leap from implementation to innovation.
The Biggest Challenge:
There is a big divide between transformation and the tactical use of AI. Everybody understands that AI can be transformational, but almost every deployment of AI today is tactical – in specific targeted projects that will typically drive cost reduction or marginal gains within 12-18 months. This, however, may end up being the greatest risk for organizations in my experience – the inability to take bold and transformative decisions.
AI may feel like a known entity for IT professionals, and innovation a tangibly beneficial frontier, but AI transformation can often be an investment into an unknown for business heads. Securing buy-in from leadership requires a wider outlook from IT leaders looking to convince stakeholders to invest in real innovation and transformation.
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