Scaling artificial intelligence: A pivotal strategy for businesses

 

Technology leaders say that scaling artificial intelligence is the top priority for data strategy, and many leaders plan to increase investment in this area to be AI-driven by 2025.

Some companies view more advanced automation, including the ability to scale artificial intelligence (AI) for data strategy, imperative to improve their business. While many technology leaders have ambitious plans to be AI-driven, there are concerns that they may not have the data capabilities to achieve those goals by 2025, a new report says.

Many organisations are at the start of their transformation journey, the report says, just beginning to uncover the efficiency, speed, innovation, and other gains that the use of AI and machine learning can generate across different functions.

CIO Vision 2025: Bridging the Gap Between BI and AI found that most respondents claim no more than limited adoption of AI uses today in all but two core enterprise functions, the exceptions being IT and finance. However, “less than 1% of the respondent companies can be considered AI-driven today”, the report said.

While many companies do not have the current capabilities to embed AI across the board, 14% of leaders in this area aim to be AI-driven by 2025, the report says. But many respondents said that rigid organisational structures and processes, along with budget constraints for new technologies, may halt progress in expanding and scaling AI use cases.

The survey that forms the basis of this report was conducted by MIT Technology Review Insights in May and June 2022. The respondents hold senior technology roles, covering 18 countries.

Even though data and budgetary concerns loom over businesses, AI is a top priority for technology leaders, the report says. More than three-quarters of the enterprise technology leaders surveyed say that scaling AI and machine learning use cases to create business value is the top priority of their enterprise data strategy over the next three years.

In order to achieve automation goals by 2025, technology leaders aim to increase investments significantly, according to the report: “[They] will increase their spending in [data security] by an average of 101% over the next three years.” Over the same period, they also plan to invest 85% more on data governance, 69% more on new data and AI platforms, and 63% more on existing platforms.

While AI development is in its infancy for many companies, survey respondents who have implemented automated functions report “solid returns from AI in a variety of areas” and that security and risk management have benefited the most from those processes, the report said.

How technology leaders can help to facilitate the transition:

Democratisation: “Many chief information officers (CIOs) are looking to … data-literate employees … to rise to this challenge. … The infrastructure modernisation that CIOs pursue should aim to widen employee access to data needed for algorithm development.”
Openness: “CIOs know that their companies’ future success in innovating with AI will rely at least in part on the data, insights, and tools they are able to source externally. Data technology that favours open standards and open data formats is well placed to facilitate such collaboration.”
Multi-cloud: “Platforms with centralised capabilities … are increasingly an option to manage complexities. And it’s hard to argue with the access multi-cloud affords to data processing power on-demand and new, cloud-based AI solutions.”
Other key takeaways from the report:

More qualified tech talent needed: As talent shortages continue to impede many companies from evolving their automation capabilities, respondents rated talent and skills development as the most instrumental investment to help companies generate benefits from AI over the next three years.
Problems with data are a main constraint: Many respondents state that improving data quality is integral to reap the rewards from AI, but “72% say that problems with data are more likely than other factors to jeopardise the achievement of AI goals between now and 2025”.
Revenue is predicted to be the most tangible return on investment: “By 2025, net additions to revenue are expected to be the most tangible form of return gained from AI — another sign of companies’ growing ambitions for its role in their businesses.”

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