The resolutions many enterprise executives made for the new year likely involved driving new efficiencies.
Having navigated the various challenges of 2023’s shifting macroeconomic climate, organizations across sectors are increasingly turning their focus toward making changes to become more efficient and work better, and to align their resources to their biggest go-forward priorities.
Agility and efficiency are key drivers of success. The integration of artificial intelligence has become widespread, as the technology can optimize resource allocation and help meet evolving customer demands.
The tech companies responsible for training and building the world’s most capable AI systems are in the same boat as the firms looking to use and deploy them. They too need to reallocate resources to core initiatives.
On Sunday (Jan. 14), news broke that Apple is closing down a 121-person San Diego-based AI team called Data Operations Annotations and relocating them to Austin, Texas.
The threat of job cuts is happening as several other prominent companies including Google, Amazon, Citigroup, and others have also announced layoff plans.
Google is reportedly laying off hundreds of workers in its ongoing cost-cutting campaign, eliminating positions in its voice assistant business, as well as hundreds more jobs among the hardware team behind its Pixel, Nest and Fitbit products, as it looks to focus on AI.
Amazon said it was laying off hundreds of employees in its Prime Video and Amazon MGM Studios division as it looks to ensure that resources are allocated to high-potential areas.
Duolingo has cut about 10% of its contractors due to its use of generative AI to create content.
Read also: AI’s Future Is Becoming Indistinguishable From the Future of Work
The paramount importance of staying at the forefront of technological advancements to ensure sustained growth and competitiveness is playing a role in some of these enterprise reorganizations.
The generative AI industry is expected to grow to $1.3 trillion by 2032 and is projected at the same time to give back workers and employees their productivity by optimizing legacy processes.
“[AI is] changing the way that people look at the operational relationship between systems and people,” then-ABBYY Chief Financial Officer James Ritter told PYMNTS in an interview published in March.
PYMNTS Intelligence’s report “Understanding the Future of Generative Al” found that enterprise AI systems could impact 40% of all working hours.
How firms best capture that impact ultimately depends on whether and where AI systems can deliver a better return on investment than existing options.
Training and support resources will need to be provided to help users transition to new AI systems. Those who see AI as a replacement for human labor rather than as a labor-saving device could risk making themselves vulnerable to savvier competition.
AI-powered systems can analyze and streamline workflows, reducing manual intervention and enhancing the speed and accuracy of processes, even going so far as to assess employee skills and match them with specific project requirements.
PYMNTS Intelligence found that 56% of consumers who feel optimistic about the impact of AI on their work-life balance believe AI will save them time. Forty-six percent of consumers who feel at least a little optimistic about the impact of AI on their work-life balance believe AI will reduce errors, while 35% believe that AI will help them communicate with others more easily.
See also: MIT Says AI Development Should Help the Workplace, Not Control It
Still, AI doesn’t represent a silver-bullet solution to long-standing woes that may have plagued enterprise processes. After all, automating an existing inefficiency won’t make that workflow any less inefficient.
“Firms need to look at [transforming their existing processes] as a kind of crawl-walk-run mentality to get to where they need to go,” Corcentric CEO Matt Clark told PYMNTS in an interview posted in June.
Many of the areas where AI technology can have an immediate, easy-win impact include the treasury department and the payments environment by helping firms automate billing and accounting reconciliations, and update customer relationship management and enterprise resource planning systems in real time without the need for manual intervention.
Since generative AI first burst onto the landscape, PYMNTS has been tracking how the innovation can impact finance departments and what CFOs are doing to use it.
As Karandeep Anand, chief product officer at Brex, told PYMNTS in August: “If you can even save some eight- or 10-people’s worth of work at the end of the quarter and finish and close the books within 24 to 48 hours [using AI], that is priceless.”
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