· 3 min read
Keep up with the innovative tech transforming business
Tech Brew keeps business leaders up-to-date on the latest innovations, automation advances, policy shifts, and more, so they can make informed decisions about tech.
One year since ChatGPT’s viral debut spawned a frenzy of research binges in the business world, many companies are not yet in good shape to actually implement grand AI ambitions.
A recent Cisco survey of more than 8,000 business leaders responsible for deploying AI in their organizations found that just 14% of companies are fully on track to put AI strategies into practice. The report, subtitled “Intentions Outpacing Abilities,” sized up AI operations across different factors like infrastructure, data, and talent to gauge progress toward goals.
The backdrop for the report is an ongoing craze around all things generative AI that has pushed businesses to invest in the possibility of automating everything from writing code to customer service. Around 97% of those surveyed said urgency to implement AI has accelerated in the last six months, with much of the pressure coming from the C-suite and boards of directors. And 84% see AI having a significant impact on business operations.
Data dearth: Yet while AI might have evolved a lot in the last year, much of the hesitance about using it might be familiar for those who’ve undertaken business digitization efforts. One of the most fraught areas is data; companies say their necessary information tends to be siloed across the organization, which makes amassing the kind of scale needed for AI projects more difficult.
There’s also the matter of data privacy and security, which is something consumers have signaled they’re worried about with AI. More than a fifth of companies have “untested, basic protocols, or no protocols” for responding to a data breach or other security incident. The good news is that 76% of companies have a high or moderate understanding of and adherence to global privacy standards.
Infrastructure issues: More than half of respondents said their tech infrastructure has limited scalability and needs to be updated or enhanced to handle the complexity of AI. And 76% said those upgrades need to include more graphics processing units (GPUs) in their data centers.
Tech-talented: More than three-quarters of respondents said they were at least “moderately well-resourced” when it comes to tech talent. But those who did lack resources said the biggest skills gap was “comprehension and proficiency of AI tools and technologies.”
Overall, outside the 14% of leaders whose companies are fully on top of AI strategies, 34% of the remaining firms ranked as “chasers,” while 48% were “followers,” and 4% were “laggards.”