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Though still in its infancy, AI already offers CIOs the opportunity to get a real-time view of their business and its customers.
The buzz around artificial intelligence (AI) can make it difficult for CIOs to consider whether certain products and services could genuinely make a difference in their organizations. But there is substance behind the hype, as numerous studies show; AI enables companies to make internal efficiencies, improve customer experience and better connect the supply chain.
All of these benefits can be found when a business successfully gets a real-time picture of all of the relevant information, including data on their partners, the supply chain, the customer journey and metrics on organizational efficiency.
According to the Harvey Nash/KPMG 2019 CIO Survey of 3,645 CIOs and technology leaders across 108 countries, 4% of organizations had a large-scale adoption of AI, 17% had a small-scale extent of AI adoption, and 20% were piloting with AI solutions. This shows that we are still at an early stage of AI truly realizing its potential.
Last year, Gartner found that 59% of IT and business professionals said they had AI deployed, and this would be set to substantially accelerate from an average of four AI projects, to an additional six this year, and a further 15 by 2022, meaning organizations would have an average of 35 AI or ML projects in place by then. This shows that while we’re at an early stage of AI adoption, companies are now moving rapidly to be leading innovators in the AI space.
The fact that many organizations are piloting with AI solutions or starting with a smaller number of projects suggests that they’re making the same considered efforts as Natural History Museum CIO Alison Davis to “start small,” testing and experimenting with AI solutions to see which products and services the organization can really benefit from.
It’s at this piloting stage where organizations also get to know how their existing infrastructure may need tweaking to enable AI to work most effectively.
By collecting trusted data across their enterprise platforms – from core enterprise systems to edge devices – AI can help businesses move faster, derive new insights and put them in a place to know more about their business and its customers.
Gartner found that concerns with data scope or quality (34%) was one of the top challenges for organizations. To make AI work effectively, data needs to be of high quality, centralized and compliant with data protection regulations. By unifying data across disparate sources, in a format and platform that can standardize this data, organizations are enabled to deliver accurate insights, building trust with their customers and employees, and reducing bias. In addition, there may be a gap in the data being collected which needs to be filled; working with the right partners and selecting the right platforms that enable organizations to find these gaps and create a comprehensive data strategy is key.
The Gartner survey found that a lack of skills (56%) was the top challenge that IT professionals cited when it came to AI adoption. AI was the third most scarce IT skill set, according to CIOs in the Harvey Nash/KPMG study. This suggests that as part of a comprehensive data strategy, organizations will need to consider their recruitment and training plans to ensure that AI can work effectively. Without the right data or people, AI’s effectiveness may be severely impacted.
In addition, there needs to be a focus on the outcomes that the business would like to achieve, whether it’s improving the customer experience, enabling a more agile workforce or making the supply chain work more efficiently. Merely using AI because it is AI will mean organizations could be trying to solve problems that do not exist.
As with every useful technology, AI solutions are not silver bullets; but they can provide organizations that have a cohesive digital strategy in place a real competitive advantage.
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