A decade of AI: From support tool to replacement

What if I told you that artificial intelligence isn't some futuristic invention from the last few years, but has been around since the 1950s? Alan Turing proposed his famous ‘imitation game’ - the Turing Test - in 1950, planting the seed for what we now call AI. The chatbots, image generators, and recommendation systems we use today are merely evolved descendants of those early experiments.

And here's the thing: if you own a smartphone, you're using AI right now. Probably without even realising it. Every time you scroll through Instagram, type a question into Google, or notice an ad that feels eerily tailored to your recent conversations, that's AI at work. It's so deeply embedded in our daily lives that we've stopped noticing it. A common person can generate images, ask ChatGPT for answers, even write their homework using these tools. So naturally, industries have gone all in. They use AI to curate your social media feed, manipulate your search results, target you with hyper-specific advertisements. For all you know, this very article could be AI-generated.

But how did we get here? And more importantly, where are we headed?

Rewind to 2020, a year that wasn't just marked by a global pandemic but also by what many now call the end of the ‘AI Stone Age.’ In January, Google unveiled Meena, a conversational model that could hold surprisingly human-like dialogue. By June, OpenAI dropped GPT-3, a model with 175 billion parameters that could write essays, code, and poems without needing extensive training for each task. And then Google DeepMind's AlphaFold cracked the protein folding problem, a scientific puzzle that had stumped researchers for decades.

Back then, AI was still largely seen as a support tool, something that helped with busywork, automated repetitive tasks, and maybe spat out a few content suggestions. When people saw AI-generated videos or images, they were amazed. "Look what technology can do!" was the common refrain. The novelty was the point.

By 2021, the tone shifted. Private investment in generative AI surged. The FDA approved 223 AI-enabled medical devices that year alone. Organisations began asking not ‘if’ they should use AI, but ‘how’ to expand its use. According to a Stanford University report, by 2024, approximately 78% of organisations reported using AI in at least one business function, up from 55% just a year before. The average company was using AI in three different areas.

Fast forward to 2025, and the landscape looks very different. By now, an estimated 88% of organisations globally are using AI in some capacity. The market value of AI in marketing alone has jumped from $12.05 billion in 2020 to $47.32 billion in 2025. Large organisations are expected to generate 30% of their outbound marketing messages using AI tools this year.

But with widespread adoption came a reckoning.

In December 2025, McDonald's Netherlands released a Christmas ad called ‘The Most Terrible Time of the Year.’ It was almost entirely AI-generated, a 45-second spot featuring distorted characters, glitchy movements, and a cynical take on holiday chaos. The public reaction was swift and brutal. Critics called it ‘creepy,’ ‘soulless,’ and ‘depressing.’

Coca-Cola faced similar fury. Despite the brand's century-long legacy of heartwarming, human-centric holiday ads, they doubled down on AI in both 2024 and 2025. Their ‘Holidays are Coming’ campaign featured entirely AI-generated polar bears and Santa Claus scenes. Hollywood writer Alex Hirsch shared, "Coca-Cola is red because it's made from the blood of out-of-work artists."

The divide seems clear: corporations see efficiency and cost savings. Consumers see something hollow, something that lacks what the brand calls Real Magic.

The numbers tell the story

As of 2025, the data on AI usage is staggering.

The industry experts noted, "If 2024 introduced AI into the marketer’s toolkit, 2025 turned it into the industry’s operating system.”

As per PwC projections, AI could contribute up to $15.7 trillion to the global economy by 2030, $6.6 trillion from productivity gains and $9.1 trillion from consumption-side effects.

Five years from now

So what happens next? Where does this trajectory take us by 2030?

By 2030, markets might transition from ‘digital-first’ to ‘AI-native’ economies. This isn't just about using AI as a tool; it's about AI becoming the foundational operating system of business itself.

Google's 2026 AI Marketing Blueprint already points the way forward. The focus moves from using AI as support to establishing it as the ‘core layer’ of operations.

Neelav Bose of Zenith India elaborated on how AI could be used in the coming years.

Advertising is expected to change rapidly as AI becomes more advanced, with emotion-aware systems using biometric and facial cues to tailor ads in real time, while virtual AI influencers, some celebrity-backed, others fully synthetic, begin to dominate social platforms. Brands may also experiment with neural and multi-sensory advertising through brain-computer interfaces that can simulate sensations beyond screens.

At the same time, autonomous marketing engines could plan and execute campaigns with little or no human input by responding instantly to live signals such as trends, weather and inventory.

As these technologies scale, consent-first and opt-in personalisation is likely to become critical, with consumer trust emerging as a key currency.

The projections are all over the map, but none of them are comforting. Goldman Sachs Research estimates that AI could eventually. Looking ahead, marketers expect AI to become a core layer of marketing operations rather than a supporting tool.

Environmental price tag

While everyone focuses on jobs, the planet is paying a different price. A single ChatGPT search uses ten times more electricity than a standard Google search.

Tech giants like Google, Microsoft, and Meta increased their collective from 2020-2023. Google's emissions alone rose by. Meanwhile, AI-related water consumption hit 765 billion liters in 2025, more than the total global demand for bottled water

The AI sector’s annual water withdrawal has reached a scale that surpasses the approximately 450 billion litres of bottled water used by the global population each year.

In By 2026, data centres are projected to consume 1,050 terawatts of electricity: a consumption level that would place them fifth on the global electricity consumption list, nestled between Japan and Russia. Currently, data centres already account for 1% to 1.5% of global electricity use and 0.6% of global carbon emissions.

If generative AI adoption continues at its current pace, AI-related electricity use could consume 1-3% of global energy demand by 2030.

Risks we're not talking about enough

As we hurtle toward 2030, several projected harms loom. AI is increasingly found tangled in the cases of the creation of AI-generated child sexual abuse material. Most recently, Grok has been caught generating obscene content on request on X.

So where does this leave us?

The decade from 2020 to 2030 represents a significant technological transformation in modern history. AI has evolved from experimental curiosity to a core industrial operating system. The marketing industry shows us what this hybrid future looks like: routine execution is automated, while human oversight focuses on strategy, ethics, and cultural nuance.

But the McDonald's and Coca-Cola backlashes remind us that efficiency isn't everything. Consumers still value ‘Real Magic’ human storytelling, authentic connection, the imperfect warmth of creativity that can't be algorithmised into existence.

The labour market remains in flux, with significant short-term pain likely for displaced workers even if new roles eventually emerge. And the environmental crisis might be the most urgent challenge of all.

As we approach 2030, the success of AI integration won't depend on the speed of adoption. It will depend on whether we can implement guardrails that prioritise moral clarity, environmental sustainability, and the preservation of human agency in an increasingly automated world.

The question isn't whether AI will reshape our lives; it already has. The question is whether we're reshaping AI in return, bending it toward outcomes that serve humanity rather than just efficiency metrics and quarterly earnings reports.