Uchenna Okpagu (Certified AI Scientist)
As a leader in AI engineering and strategy who has spent the last few years building and navigating the shift toward agentic AI, I see 2026 as the definitive turning point for our industry.
If 2025 was defined by experimentation and pilot AI projects, 2026 will be the year of full-scale, production-grade AI adoption. Organisations are moving past the hype and focusing on one core metric: high Return on Investment.
What does this mean for businesses? Rather than AI as a buzzword, it has become a core business enabler. The most important aspect is the measurement of its impact. In subsequent articles, I will spotlight measurement metrics for AI-enabled initiatives.
Here is how I see the landscape shifting for the major players and the broader ecosystem:
Agentic AI Stack for Businesses
In 2026, the most successful businesses will be those who curate and adopt the most effective agentic AI stack.
Strategic tool selection is now a primary driver of success. It is no longer enough to just “adopt AI.” You must map specific agentic tools to your specific use cases to win.
For example, your engineering team should be using coding agents like Claude Code, Gemini CLI, or OpenAI Code to accelerate development by over 15x. This does not just shorten time to market. It allows you to scale output without the traditional overhead of massive hiring cycles.
Similarly, your product designers should be using prototyping tools like Lovable and FigMake to move from concept to reality in hours, not weeks. Your branding and marketing teams must leverage models like Google Veo to produce high-definition media assets via simple prompts.
The Big 4
The competitive landscape has moved from a general arms race to a strategic division of domains. We will continue to see each provider double down on what they do best.
- Anthropic’s Claude: Anthropic has firmly secured its niche in the world of agentic coding. With Claude Code, they are moving beyond simple code completion to provide agents that can reason through complex repositories and handle end-to-end engineering tasks.
- Google Gemini: Google continues to lead the pack in native multi-modal generation. Their ability to seamlessly blend image, video, and audio reasoning remains the gold standard for creative and complex visual workflows.
- OpenAI: OpenAI is successfully positioning ChatGPT as the central OS for AI. By deepening integrations into everyday applications, they are turning their platform into a unified command centre where the AI orchestrates tasks across your entire software stack.
- Meta AI: Meta is dominating the hardware layer. Their focus on wearable AI is making the technology ambient and accessible, moving it from our screens into our physical environment.
AI Market Consolidation
We are also entering a significant phase of mergers and acquisitions. The market is maturing, and we will likely see specialised startups like ManusAI or Genspark being absorbed into larger ecosystems. For leaders (Microsoft, Google, OpenAI, etc) in this space, these acquisitions are less about acquiring users and more about integrating specialised agentic capabilities into broader enterprise platforms.
Implications for Individuals
From my perspective as a leader in AI transformation, the most critical takeaway is for the individual. Whether you are a student or a seasoned professional, maximising your use of AI is no longer a secondary skill; it is a professional imperative.
To “stand taller” in 2026, you cannot treat AI as a tool you occasionally consult. You must become an orchestrator of these technologies. In a world where businesses are scaling through AI agents, your value will be defined by your ability to lead, govern, and innovate alongside them.
Risk Management and Governance
For businesses moving to full-scale AI adoption, 2026 brings a necessary dose of regulatory reality. This is the year the majority of the EU AI Act provisions move into full enforcement. By August 2026, strict requirements for high-risk systems in sectors like fintech and recruitment will become mandatory.
For those leading AI transformations, this means moving beyond simple deployment to rigorous risk management and governance. We are now legally required to maintain deep technical documentation, ensure human oversight, and provide clear transparency for all agentic AI decisions. In 2026, governance is no longer a hurdle. It is the essential framework that allows us to build the trust needed for high-stakes enterprise environments.
Next Steps for Businesses
In 2026, the real challenge is balancing the gas and the brakes. While we are pushing for full AI adoption to capture that high ROI, we must adopt an AI safety mindset as a core imperative.
This means running a company-wide AI Risk Audit (KYAI) to identify and address Shadow AI and data privacy leaks before they escalate. When we build on the pillars of Safety, Trust, Reliability, and Fairness, we aren’t slowing down; we are building the structural integrity needed to innovate faster.
Innovation without safety isn’t growth, it’s a liability.
