According to a report by web security company Indusface, backed by data from Capital Economics and DCMS, 77% of businesses globally are either using or exploring artificial intelligence (AI). On top of this, nearly half of top tech businesses identified AI as their most substantial expenditure.

As the technology continues to advance relentlessly across various sectors, concerns over potential over-reliance on the technology have been raised. 

“Whilst AI can help businesses conceptualise and build code, AI should still be used as a sidekick, not a dependent, especially for software development,” warns Venky Sundar, founder and president of Indusface.

According to the study, the top AI-reliant industries are: 

• Legal: 30% of UK law businesses already embrace AI. AI in the legal sector is utilised for research, analysis, due diligence, efficiency, and cost reduction, enhancing the quality of legal services.
• IT and Telecoms: This sector follows closely behind, with 29.5% of UK businesses integrating AI. Benefits in this sector encompass network optimization, predictive maintenance, customer service automation, security, and data analytics.
• Finance and Accounting: Over a quarter (26%) of UK businesses in this field are actively utilising AI. AI is instrumental in tasks such as fraud detection, credit risk assessment, financial reporting, tax preparation, and customer service.

Following these are media, advertising and Sales, transport and distribution, manufacturing, education, construction, real estate, hospitality and leisure. 

“Any sectors powered by tech as a key element of their business, from farming to finance are at risk of relying too much on AI,” said Sundar.

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He points out that data-intensive industries requiring analytics, such as consumer engagement, credit risk assessment, and consumer understanding, are likely to experience faster AI adoption.

“If you go to market with the POC (proof of concept), there could be serious consequences around application security and data privacy. AI could give you code that is vulnerable to attacks, as secure coding practices are rarely followed.”

Sundar stresses the need for separate knowledge bases for productivity use cases and defence use cases and emphasises human oversight to ensure diverse and secure datasets.

As AI continues to reshape industries, businesses must tread carefully to maximise its benefits while safeguarding against potential vulnerabilities and dependencies.