New Research Report Shows Rapid, Widespread Adoption of Generative AI

The hype around artificial intelligence is reaching an unprecedented level. Sometimes in technology, reality never matches the hype. With AI, however, I think it’s justified.

I view the adoption of AI as similar to the adoption of internet technologies. We talked about the Internet, promoted it, created economic reports, and then we stopped talking about it because it became integrated into everything we do. From an adoption perspective, we’re not there yet with AI, but a recent report shows that many organizations are already using AI, and it’s close to adoption at large scale in most sectors of activity.

C1, a global technology solutions provider focusing on “improving connected human experiences,” released a report this month showing how quickly and pervasively generative AI is being used by businesses. The report “The era of connected human experience powered by AI is here» examines how organizations are using AI to improve automation, develop new products and services, create software and much more.

C1 surveyed more than 500 decision-makers across multiple sectors, including education, finance, healthcare and manufacturing. The results show the strategic role that AI already plays. Here are some highlights:

• 100% of organizations surveyed are creating new KPIs to monitor AI applications in their business. The main focus is on improving the quality of interactions.
• 99% have accelerated AI adoption and 51% of executives surveyed said they are “significantly accelerating” the integration of AI across their operations.
• 80% of respondents said that AI generation is “essential to improving employee collaboration and work quality.”
• On the customer side, 76% of organizations believe that AI will be “integral to improving the quality and experience of customer interactions.”

Of the above data points, the first is the most notable. Creating new KPIs will help businesses understand how to measure processes in the AI ​​era. For example, with contact centers, a tried and tested KPI is “average handle time” or AHT, to measure the duration of a customer call.

With virtual agents handling mundane tasks, AI-powered contact centers see AHT increase as real agents perform more complex tasks. Early adopters of AI are using metrics like upsell opportunities or AI generating CSAT as new metrics. This is something that all businesses will need to do and the data shows that this is already happening.

Not a one trick pony

One of the most interesting aspects of the research is the diversity of ways in which organizations are leveraging AI generation for their mission-critical activities.

• 85% use AI generation to improve automation.
• 84% use it to co-develop products and services.
• 84% say generation AI helps them develop code.
• 68% use it for virtual assistants or co-pilots.

Given how quickly the AI ​​generation has taken hold in many companies, it is interesting to note that when it comes to its effects on workers, 90% of business leaders who participated in the survey claim that AI “enhances the human experience in the workplace.” Examples cited include the adoption of virtual assistants, automation solutions, and tools to support dynamic workflows.

An interesting dynamic is how AI changes work. If AI saves workers time and gets tasks done faster, should companies change people’s goals? For example, if salespeople are no longer required to put information into customer relationship management services because AI can automate that, should we expect more meetings and deal closures? I’ve asked this question of CEOs, HR managers, and line-of-business leaders, and there is no consensus opinion, but it appears that workers’ goals will need to be adjusted.

Leaders are not unaware of the risks linked to the AI ​​generation

As with any new technology, it may take time to determine with a high degree of certainty whether the innovation is harmless and beneficial or potentially harmful. This process could evolve more quickly with the AI ​​generation than with almost any other technology that has appeared on the market in decades.

Even as organizations rapidly innovate with generative AI and deploy it at scale, the report acknowledges that business leaders “must recognize the potential risks and challenges of adopting generative AI.” Areas where the report says “organizations should exercise caution” include data privacy, intellectual property issues and cybersecurity risks. According to survey respondents, the “shortage of skilled professionals” in AI development, deployment and maintenance is linked to these concerns.

Some 65% of respondents said their organization had “reviewed its cybersecurity protocols” regarding potential AI risks to address these concerns. C1 notes in the report that early adopters’ caution “underscores the importance of strategic planning and implementation of AI.”

This is a case where security and compliance must be integrated into the design of new AI-enabled processes. Often, companies adopt new technologies and security issues are investigated in post-production. Since the risks of AI are so high and will be public, it is prudent to include it in the deployment.

Early adoption of AI is linked to first-mover advantages

Survey respondents who reported “high to very high usage” of Gen AI come from a broad group of industries:

• Utilities: 86%
• Health care: 81%
• Manufacturing: 75%
• Finance and insurance: 68%
• Reception: 68%
• Education: 65%

What’s notable about the industries above is that those with the highest application adoption are typically slow, with processes filled with “human latency.” AI will have a huge ROI in these verticals. I recently spoke to a hospital administrator who told me that each missed appointment costs the organization thousands of dollars due to staffing and equipment costs. AI is used at this facility to automate patient contact and appointment confirmation, resulting in a 90% reduction in missed appointments.

C1 cites “potentially significant” implications of being a pioneer in generational AI. “Organizations that learn from their generative AI implementations have an advantage over those that do not use generative AI-based capabilities. Those who gain experience do so at an accelerated pace, while those who approach generative AI implementation cautiously risk falling too far behind. We saw this happen in the Internet age, when companies we’d never heard of before disrupted tried-and-true providers. Expect to see the same thing with AI.

The era of AI has arrived and will change every aspect of our lives. I asked business and IT leaders for recommendations on how their peers should get started in AI if they haven’t already. Their advice is to jump in and start trying things. There is an expression that some people make things happen, others watch things happen, and the rest wonder what happened. You don’t want to be in the latter category with AI.

Zeus Kerravala is a principal analyst at ZK Research, a division of Kerravala Consulting. He wrote this article for SiliconANGLE.

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