According to a new study into AI usage across enterprises, most businesses are well underway with AI experimentation. Despite this, many still lack an understanding of the use cases to deliver business value, as well as the data infrastructures for making AI a success across the enterprise on a sustainable basis.
The survey, commissioned by Mindtree, gathered data from 650 global IT leaders from key business markets and found that 85% of organisations have a data strategy and 77% have implemented some AI-related technologies in the workplace. Of those respondents, 31% are already seeing major business value from their AI efforts. Organisations are achieving their vision to industrialise AI, but many can do more to gain real business value.
Greater focus is needed on use cases that deliver business value
When implementing an AI strategy, there’s a pressing need for use cases to demonstrate business value. The survey revealed that 16% of enterprises globally focus on a pain point and then define a use case, with smaller organisations (13%) being less likely to focus on the business impact compared with their larger counterparts (18%). With all the pressure to harness AI, many organisations are experimenting but not all have found the formula to deploy at scale and add significant value.
The survey found there are certain business functions such as sales (35%) and marketing (32%) gaining the most value from AI, as it accelerates the delivery of improved customer experiences. The most popular technologies deployed by global organisations are machine learning (34%), chatbots (34%), and robotics (28%).
Success with AI means merging rapid experimentation, organisational agility and skills
AI is already delivering measurable business benefits, but the majority of enterprises have yet to find a formula for repeatable success. An important requirement for enterprises to successfully start their AI journey is to experiment with different use cases and technologies with agile and rapid innovation methodologies. Just over a quarter (29%) of the enterprises surveyed said they are agile enough to rapidly experiment with AI, with large organisations (39%) having an edge compared to their smaller counterparts at 19%.
Progressive enterprises are spending 25% of their IT budget on digital innovations with a focus on use case definition, experimentation, and operationalisation for scale. Businesses also understand the need to upgrade and refresh their skills to capitalise on AI. 44% say they will hire the best talent available externally, 30% have partnerships with academia, and 22% run hackathons to solve data challenges and identify potential candidates.
The AI-led enterprise – it’s all about data
Finding the right use cases and building alignment and support for AI initiatives are critical, but data is the make-or-break variable when it comes to scaling AI across the enterprise. Businesses need to modernise their data infrastructure, architectures and systems, along with an overarching data strategy and robust data governance processes. The survey revealed more than half (51%) of large enterprises say they don’t fully understand the data infrastructure needed to implement AI at scale, while 6 out of 10 organisations believe their data infrastructure and architectures are immature and not well positioned to deliver business value.
“The potential of AI to disrupt, transform and rebuild businesses is clearly felt in the C-Suite, even if it is not yet fully understood,” said Suman Nambiar, head of strategy, partners and offering for digital at Mindtree.
“Business and technology leaders are increasingly expected to prove business value, unlock the power of their data, and define their AI strategy and roadmap. To thrive in the Digital Age, businesses must be agile and unafraid of failure. They must also constantly refine their understanding of how AI will give them a competitive edge and deliver real and measurable business value to maximise their investment in these disruptive and powerful technologies.”
Methodology
The online survey was conducted by Censuswide and the data was gathered from 650 global IT leaders, with an equal breakdown of 325 respondents from the UK and US.
