The Implications When AI Becomes As Common As Electricity

AI use is almost commonplace. More than seven in ten respondents to a recent McKinsey survey, 71%, say their organizations regularly use genAI in at least one business function, up from 65 percent in early 2024. On the consumer side, 52% of US adults now use AI large language models such as ChatGPT, a survey out of Elon University shows.

In essence, we can almost “start thinking of AI like we think of electricity,” said David Nicholson, chief technology advisor with The Futurum Group. “As the cost of generation and delivery declines, it will become increasingly ubiquitous. Everything will be infused with AI.”

Such widespread adoption is just half the story. The democratization of AI means new roles, new capabilities for innovation across a wide spectrum of industries – no matter how small the company.

“Small businesses can now use AI like bigger companies,” said Jason Wingate, founder of Emerald Ocean Ltd. “Think personalized customer service bots, product recommendations, and customer behavior predictions.”

Think back to the initial introduction of the personal computer in the early 1980s. “We’re at the point where AI tools are becoming as common as spreadsheets were after PCs came out,” said Wingate. “Just like how nobody predicted Excel would change business forever, we’re probably not seeing half of what’s coming with democratized AI.”

While the journey ahead with AI “will be marked by challenges, turbulent times, and difficult decisions—especially for those unprepared—the ultimate outcome will be a better, more evolved world,” said Ben Lytle, co-founder of The Ark Project. “AI will accelerate meaningful work, personal growth, learning, and psychological evolution.”

For example, the long-sought market of one is now a reality – a “treatment that both delights and annoys us as we shop online will be extended to all aspects of personal health and wellness,” said Nicholson. “Every detail about diet, exercise, sleep and pharmaceuticals will be gathered and analyzed.”

Healthcare in particular is set for major disruption, and hopefully greater innovation and reform. “As AI becomes cheap, accessible, and capable of human-like reasoning, we’re on the verge of hyper-personalized experiences that were previously impossible,” said Vincent Koc, an industry consultant and lecturer at the University of New South Wales.

Koc notes that he is “working on precision health use cases with medical companies in the US and Australia, where AI is synthesizing patient data: food, lifestyle, genetics, medical history, into a real-time, personalized healthcare experience.” This means the rise of AI-driven doctors that can augment clinicians’ work.

Thanks to the plunging costs of providing AI services – as evidenced with the DeepSeek announcement in January – the innovation possible through AI is now accessible without massive hardware investments. “Significant progress can be made without billions in funding or cutting-edge hardware,” said Peter Morales, CEO of Code Metal. “This marks a shift where smaller players can build domain-specific reasoning models, democratizing what was once exclusive to well-funded AI labs.”

AI is “not just for tech giants anymore,” Wingate agreed. “For example, a local shop could use AI to track customer preferences and automate reordering, something that used to need expensive enterprise systems.”

Nicholson anticipates major changes coming for the workplace as AI becomes ubiquitous and commonplace. “In business, individual contributors will need to become managers of agents,” he said. “This will drive productivity and efficiency to levels that are impossible today. The ultimate example of this, I predict, will be the era of an organization with a single human at the center, with only cyber-agents as employees, generating a billion-dollar valuation.”

AI workers and AI-augmented staff “will push us further into asynchronous collaboration,” Koc agreed. “Meetings, decision-making, and even workplace rituals may become more AI-mediated, reducing the need for synchronous coordination and instead letting AI handle workflows in the background.”

Ubiquitous AI will also bring us the power of reasoning engines in small-footprint devices as well. “Companies that develop apps for devices such as mobile phones and the IoT can benefit from lesser energy-consuming computational requirements and provide increased AI capabilities more quickly,” said Allen Drennan, co-founder and principal at Cordoniq. “This can open doors to developing devices more rapidly and lowering costs to consumers in the process. New device markets will arrive to fill many niche and potentially large market spaces that were previously not readily accessible without cost-effective AI advancements.”

More power-efficient small-footprint AI solutions “can bring a rapid transformation to nearly all industries, including business software, fintech, manufacturing, education and much more,” Drennan added.