Ahead – 4
Pratik Bhadra: “Welcome to “Agentic Marketing.” This marks the next leap, where autonomous AI agents transition from executing simple tasks to managing complex workflows. As I’ve written before, this isn’t just a “co-marketer” that offers suggestions; it’s an agentic system that can independently orchestrate journeys, allocate budgets, analyze data and deploy campaigns based on a human marketer’s strategic goals… The core problem with marketing’s “AI 1.0” phase is that we’ve been bolting new technology onto old-world processes. We use GenAI to write an email, but we still send it using 20-year-old retention marketing channels like email and SMS designed for “batch and blast” segmentation. An “agentic” system upends this model. A human marketing leader doesn’t build a 10-step journey flow; instead, they give the AI agent a goal. One example I have used looks like this: “Reengage all dormant customers who purchased in Q4 last year. Your budget is $10,000, the goal is a 15% reactivation rate, and you are not allowed to discount more than 20%.” This transformation has moved us from traditional CRM-based marketing to the intermediate predictive AI-based marketing world we’ve been in for the past decade, and is now transitioning into goal-based autonomous marketing.”
Alex Wang: “AI Moves From “Feature” to Workflow Layer. The highest-performing teams aren’t shipping AI buttons. They’re embedding AI inside the actual process: support routing, financial operations, sales planning, engineering sprints, customer success playbooks. It’s the same theme the Glean AI Transformation report surfaced: AI dies when it’s bolted on; it works when it’s embedded.”
John Chambers: “In 2025, AI went mainstream. In 2026, every employee, across all industries, will use AI regularly. AI is unlike any other tech transition we’ve ever seen – faster, more disruptive, more transformative. This isn’t incremental change; it’s a revolution reshaping even the most traditional verticals. For leaders, this is the moment to break away and emerge as a leader that is redefining the industry as a whole. The choice is clear: disrupt or be disrupted; adopt AI or get left behind. And it doesn’t stop at simply adopting AI – it’s the responsibility of your company to train and empower every employee, from entry-level employees to the C-suite, to leverage it. Those who enable their workforce will lead and those who don’t will lose.”
Bernard Marr: “AI In The Physical World. This trend covers the increasing influence of AI on the physical systems and mechanisms that constitute the world around us. It includes autonomous vehicles, which will undoubtedly become increasingly prevalent, as well as humanoid robotic workers that will take on physical labor in warehouse, construction and healthcare settings, and the web of interconnected devices that makes up the increasingly sprawling “internet of things”. In 2026, AI isn’t just powering apps on our phones and the software we use on PCs. As regulatory and security guardrails mature, it’s sharing our homes, industries and workplaces, becoming a tangible presence in our world, and redefining our interactions and relationships with all forms of technology.”
David Ulevitch: “Building the AI-native industrial base. America is rebuilding the parts of the economy that create real strength. Energy, manufacturing, logistics, and infrastructure are back in focus, and the most important shift is the rise of an industrial base that is truly AI native and software-first. These companies start with simulation, automated design, and AI-driven operations. They are not modernizing the past. They are building what comes next. This is opening major opportunities in advanced energy systems, robotics heavy manufacturing, next-generation mining, biological and enzymatic processes that produce the precursor chemicals every industry depends on, and much more. AI can design cleaner reactors, optimize extraction, engineer better enzymes, and coordinate fleets of autonomous machines with a level of insight no legacy operator can match. The same shift is reshaping the world outside the factory. Autonomous sensors, drones, and modern AI models can now give continuous visibility into ports, rail, power lines, pipelines, military bases, datacenters, and other critical systems that were once too large to manage comprehensively.”
- The Path Clears for Two $1T+ AI IPOs
- A $50B+ AI Software Acquisition Reshapes the Market
- AI’s Soaring Power Demand Collides With Energy Constraints
- 50 AI-Native Companies Hit $250M ARR as Hypergrowth Accelerates
- AI Takes Over Music & Lands a Grammy
- Open, Small and World Models Gain Significant Market Share
- Robotics Adoption Ramps Slowly as Industrial Use Cases Lead
- AI Becomes an Even More Critical Driver of Modern Defense Strategy
- Cybersecurity x AI – Securing the New Attack Frontier
- The AI Bubble Debate Rages On
David Cahn: “My prediction for 2026 is that it will be a tale of two AIs. On the one hand, it will be a year of delays, first in data center buildouts, many of which will fall behind schedule, and second, in the AGI timeline. At the same time, AI adoption will continue its relentless rise. In 2025, startups coined the idea of a “$0 to $100M” club of rapidly scaling AI companies; in 2026, we’ll begin to talk about the “$0 to $1B” club.”” On the second AI: “The Relentless Drive Toward AI Adoption. The best AI startups are moving with extreme efficiency—many are earning north of $1M in revenue per employee. This implies market pull vs. a push sale. Today’s entrepreneurs are building “self-improving” companies—they are themselves using AI agents for functions like legal, recruiting, and sales—creating an ecosystem flywheel effect. AI app companies are also riding a compute cost curve that should drive incremental margin improvement, especially as new data centers come online between now and 2030. Finally, with enterprises facing adoption fatigue on DIY implementations, startups are gaining even more momentum.”
Battery Ventures: “While 2024 was dominated by capital-intensive model training, the center of gravity is shifting to inference. As agentic applications—which autonomously plan and execute complex workflows—come online, they will consume vastly more compute power at runtime. We believe this development will continue to drive revenue as a myriad of new agentic applications hit the market. We are also seeing the walled gardens of closed models challenged and believe open models (like that of Reflection AI* and DeepSeek) will grow in adoption, fueling a more diverse AI ecosystem.”
Bessemer Ventures: “The browser will become AI’s control center. AI has already made its way into the browser through assistants and early agentic tools. The next step will be far more transformative. We predict the browser will evolve from today’s basic AI integrations to a full execution environment where agents run tasks, maintain context across sessions, and coordinate workflows across the apps we use every day. In short, the browser won’t just display the internet. It will run it for you.”
SaaStr list:
- 50%+ of B2B Sales Teams Will Shrink in Size
- AI Agents Will Handle 40–60% of Customer Interactions
- “Vibe Coding” Becomes the Default Way to Build Software
- The Traditional SaaS Exit Model Breaks Down
- AI Gross Margins Rise to SaaS Levels (65–75%)
- Customer Support Becomes a Profit Center
- Token-Based and Hybrid Pricing Models Become Standard
- 2026 Becomes the Biggest IPO Year in Tech History
- AI-Native Companies Achieve 3–5× Revenue per Employee
- The First $1 Trillion AI Company Emerges
- Enterprise AI Finally Moves from Pilots to Production
- Decision Traces Become the New Data Moat
- AI Security Becomes a Board-Level Imperative
- SaaS Incumbents Fight Back
- Agents Eat E-Commerce
- Gemini Overtakes ChatGPT in Consumer Usage
- An AI Lab Goes Public
- Cursor-Like Interfaces Become the Default
