Ahead – 2
Claude
2025 was about capability breakthroughs: reasoning models, efficient training (DeepSeek), frontier competition (GPT-5, Gemini 3, Claude 4.5), and AI agents moving from demos to deployments. 2026 will be about operationalization: proving ROI, scaling agents across enterprise workflows, rewiring discovery (search, commerce, marketing), and the inevitable correction as hype meets reality.
- Agentic Commerce Becomes the Dominant Shopping Paradigm
The year 2025 will likely be the last consumers shop as they do now. Agentic AI is reshaping commerce by making shopping faster, smarter, and effortless. By next holiday season, most shopping journeys will begin, evolve, or end with AI agents.
McKinsey estimates that agentic commerce could influence up to $3 to $5 trillion annually in global retail sales by 2030.
By 2028, AI agents will command $15 trillion in B2B purchases, according to Gartner. Autonomous buying systems, machine-to-machine negotiation, and data-verification frameworks are moving into the mainstream.
What to watch: The brands that optimize for agent discoverability—clean data, structured catalogs, seamless APIs—will win. Traditional SEO and brand advertising will matter less when an AI agent is deciding what to recommend.
- AI Moves from Proof-of-Concept to Proof-of-Impact
2026 will be the moment to move from proof-of-concept to proof-of-impact, ensuring AI drives measurable outcomes, trust, and collaboration at scale, whilst laying the foundations for larger-scale transformation to follow.
There is—rightfully—little patience for “exploratory” AI investments. Each dollar spent should fuel measurable outcomes that accelerate business value. We expect that to change in 2026. We now know what good agentic AI looks like—it has proof points like benchmarks that track value that matters to the business.
What to watch: CFOs will demand ROI metrics, not innovation theater. Organizations that can demonstrate P&L impact from AI will accelerate; those still “experimenting” will face budget cuts.
- 40% of Enterprise Apps Will Use Task-Specific AI Agents
Gartner predicts that 40% of enterprise applications will leverage task-specific AI agents by 2026, compared to less than 5% in 2025.
Hyper-automation in 2026 will be driven by advanced AI, process mining and cross-platform orchestration—automating complex, end-to-end workflows with minimal human input.
What to watch: The agent ecosystem will mature rapidly. Expect standardized protocols for agent-to-agent communication, shared memory frameworks, and governance tools for managing fleets of AI agents.
- “Search Everywhere Optimization” Replaces Traditional SEO
Search Everywhere Optimization will replace traditional SEO as the dominant visibility strategy. As AI search tools like ChatGPT, Perplexity, and Gemini continue to gain traction—and platforms like TikTok, Amazon, and YouTube evolve into primary search destinations—discovery will no longer revolve around a single search engine.
Discovery has fractured far beyond the ten blue links. Users now bounce between TikTok, Reddit, YouTube, ChatGPT, Gemini, and AI assistants before ever reaching a website. The content performing best in 2026 is the kind AI can’t easily imitate: opinionated commentary, first-hand experience, data-rich insights, and multimedia storytelling.
What to watch: Brands will need to optimize for AI citations, not just rankings. Structured data, entity recognition, and “answerability” become the new currency of visibility.
- Domain-Specific Language Models Outpace General-Purpose LLMs in Enterprise
CIOs and CEOs are demanding more business value from AI, but generic large language models often fall short for specialized tasks. Domain-specific language models fill this gap with higher accuracy, lower costs, and better compliance. By 2028, Gartner predicts that over half of the GenAI models used by enterprises will be domain-specific.
These are specialized AI models trained on the vocabulary, rules, and operational context of a particular industry or function. Instead of trying to be universal, they specialize—delivering higher accuracy, reducing ambiguity, and staying compliant with domain standards.
What to watch: Vertical AI companies will emerge in every industry—legal, healthcare, finance, manufacturing—with models that outperform GPT-5 on industry-specific tasks.
- AI Becomes a True Scientific Collaborator
In 2026, AI won’t just summarize papers, answer questions and write reports—it will actively join the process of discovery in physics, chemistry and biology. AI will generate hypotheses, use tools and apps that control scientific experiments, and collaborate with both human and AI research colleagues.
Examples include MatterGen and MatterSim, AI foundation models that help create new materials and simulate how they will perform, accelerating materials discovery for innovations like carbon capture and high-performance batteries for clean energy.
What to watch: Expect breakthroughs in drug discovery, materials science, and climate modeling as AI moves from analysis to active experimentation.
- The AI Bubble Shows Signs of Correction
After several years of frenetic investment and breathless expectations, signs point to a necessary correction in the AI marketplace. Venture-backed startups that promised transformative capabilities without sustainable business models will feel the pressure first. This “pop” will not signal the end of AI—far from it. Instead, the market will mature as weaker players fold, stronger innovators expand, and investors prioritize practical value over hype.
The race to build massive data centers has accelerated at unprecedented speed. As efficiency improves and organizations shift from training to inference, pockets of overcapacity may emerge.
What to watch: Consolidation in the AI startup space, more rigorous due diligence from investors, and a flight to quality over hype. The survivors will be those with real revenue, not just impressive demos.
- Critical Thinking Skills Atrophy Forces “AI-Free” Assessments
Through 2026, atrophy of critical-thinking skills due to GenAI use will push 50% of global organizations to require “AI-free” skills assessments. As automation accelerates, the ability to think independently and creatively will become both increasingly rare—and increasingly valuable.
By 2027, 75% of hiring processes will test AI proficiency. Meanwhile, 50% of global organizations will require “AI-free” assessments by 2026 to ensure candidates can demonstrate independent reasoning and critical-thinking skills without machine assistance.
What to watch: A bifurcation in talent markets: “AI-augmented” roles that maximize human-AI collaboration, and “AI-independent” roles where human judgment is the premium skill.
- A Brand’s AI Becomes Its Identity
“By 2026, brands won’t be defined by logos or slogans; they will be defined by their AI. These customizable agents will become the ultimate brand ambassadors: smart, personalized, and continuously evolving with every exchange. The brands that win will be the ones whose AI delivers a consistently exceptional experience.”
“With popular consumer chatbots getting more agentic by the day, users are already growing accustomed to digital interactions informed by history, preferences, and personalized context. In contrast, generic experiences are starting to feel more and more broken.”
What to watch: Brand equity will increasingly be measured by the quality of AI interactions. Customer experience teams will merge with AI development teams.
- AI Within Search Becomes 3X Greater Than Standalone AI Tools
In 2026, daily usage of AI within search will be three times greater than any standalone AI tool—reshaping how people can discover information.
Hardware heats up: inference—the running of AI models—will make up two-thirds of AI compute by 2026. Nearly $100 billion will be invested globally in sovereign AI compute in 2026.
What to watch: The battle for AI-integrated search will intensify. Google’s AI Overviews, Bing Copilot, and ChatGPT Search will compete for the default discovery layer. The winner controls the gateway to consumer attention.
