I even use it to collaborate in writing here and there when I'm stuck or need help untangling a thought that my very overcrowded brain needs a little help with.
Which happens more than I'd care to admit, considering it often looks like a drawer full of cables with no organisational system known to man.
My honest opinion is that we can no longer ignore these tools. And if we want any fighting chance of survival (occupationally speaking), we have to learn to work alongside them, not against them. Plus, If you can leverage these skills early, you're at a major competitive advantage.
Moving on. This was my prompt:
Based on all the articles I've written and sent you, and what's happening on the internet today in tandem with your analysis, what do you predict for marketing in 2026?
The results I got were unsurprisingly sharp, and grounded in what's unfolding in the industry right now. So here's my take (of ChatGPT's take):
Why: Generative and automation tools are moving from experimentation into core planning, creative production, localisation and reporting. Treat AI as infrastructure that scales output and analysis but still needs human strategy and taste.
Do: Build an AI playbook. Include who uses what tool for which job, guardrails for brand voice, and a human review step for every customer-facing asset.
Why: Platforms (Meta among them) are actively developing end-to-end AI ad tooling so advertisers can submit an asset and goals and let AI generate and target the campaign. Expect this to be widely available by 2026.
Do: Experiment with "AI-first" pilots on low-risk budget, then compare creative lift and CPA to human-made campaigns. Use these pilots to set quality thresholds before scaling automated campaigns.
Why: Reels/TikTok/Shorts dominate watch-time and distribution; platforms continue to push video-first ranking changes. Attention is scarcer; formats will evolve but short-form still wins.
Do: Optimise for platform-native moments not repurposed long-form. Own a 6-12 second "brand hook" template and iterate 20+ variants per quarter.
Why: Chrome's cookie plans have shifted but the industry still moves toward durable, privacy-preserving approaches and first-party signals. Marketers must plan for multiple identity solutions.
Do: Double down on owned channels and progressive profiling. Create a privacy-first data strategy: consent flows, loyalty value exchange, server-side event collection.
Why: According to Onclusive, AI and frequent ranking changes make visibility rules opaque and unstable. Winning means supervising AI systems and adapting faster than competitors.
Do: Build a rapid-test cadence (1-2 week experiments), assign an "algorithm owner" to monitor rank shifts and translate them into tactical playbooks.
Why: User-generated authentic content often outperforms studio polish for trust and scale. Expect platforms and ad products to lean into creator-native formats.
Do: Treat creators as an owned channel. Build long-term partnerships, provide simple creative briefs, and run creator-first ad tests to compare ROAS vs in-house creative.
Why: Consumer research points to increasing friction with algorithmic personalisation; people will reward transparency and human context.
Do: Put transparent signals in your comms: why you recommend something, what data you use, and give people easy controls. Use human stories to balance algorithmic optimisation.
Why: This is the most important point here. As more brands use the same toolset (88% of marketers use AI daily), distinctive creative concepting and brand intent will separate winners from noise.
Do: Invest a tiny % of revenue into "creative R&D": high-concept experiments with strong human direction. Make a simple rubric to judge not just execution but distinctiveness.
Why: Economic uncertainty and platform changes push brands to favour performance guarantees, flexible terms and blended measurement across ecosystems.
Do: Renegotiate with vendors for outcome KPIs. Diversify media partners and marry incrementality testing with MMM (mixed media modelling) to prove long-term value.
Why: The tech that helps scale personalisation also increases risk (misinfo, hyper-targeting). Expect higher scrutiny and new platform policies.
