The 2026 artificial intelligence blueprint: Thriving in the era of Agentic AI

What began in 2024 as creative experimentation with artificial intelligence (AI) to explore its potential impact on businesses, shifted in 2025 to a focus on return on investment (RoI), demonstrating that the excitement surrounding AI is aligned with responsible implementation and real business value. In 2026, enterprises will enter the scale phase of AI, leveraging early successes to achieve a systemic advantage.

India is at a defining moment in its Viksit Bharat mission and is building one of the strongest global foundations for AI-driven growth. After years of experimentation and isolated pilots, organizations are now moving towards full-scale operationalisation. IDC predicts that AI investment in India will grow at a CAGR of 33.7% over the next five years, one of the fastest-growing technology investment areas in the country, expected to generate an estimated economic impact of over $115 billion by 2027.

With the growth in AI, two things are broadly on the horizon: extending RoI from the level of individual projects to comprehensive, strategic AI ecosystems, and Agentic AI. The former reflects the maturing of the enterprise itself, and the latter that of maturing technology.

AI acceleration: From point zero to Agentic AI evolution

For businesses, the real impact lies in AI’s ability to break out of fixed workflows and operate as a proactive problem solver that once required human oversight. This fundamentally changes how organisations approach scale, efficiency, and decision-making.

According to an Ecosystm, a digital research and advisory company, businesses in India are actively piloting and deploying Agentic and Generative AI across customer experience, marketing & communications, operations, and IT. With customers as the primary focus, the most evaluated use cases are interactions with customers across channels, reported by 69% of organisations, improving chatbot responses at 58%, and generating marketing content at 65%. As systems mature, Agentic AI will evolve as a trusted operational partner, reshaping collaboration, accelerating decisions, and redefining how value is created across the enterprise.

By 2026, AI agents will be an integral part of the workforce, and managing them will feel more like mentorship than programming. Enterprises will onboard AI agents in much the same way they do new human employees--by providing them with access to contextual documents, allowing them to observe workflows, assigning them small tasks, and offering continuous feedback to help agents learn and grow. AI Agents as co-workers will extend to the full employee lifecycle, including performance reviews and even "promotions" where agents will be granted more autonomy and responsibility as they prove their reliability. We will even see senior manager agents emerge who govern and validate the work of other agents — creating a dynamic, self-improving AI workforce that learns and evolves right alongside the supervision of human colleagues.

Breakthroughs that will redefine AI and data

The next wave of AI breakthroughs will redefine not just technology but the way businesses operate, compete, and deliver value. Agent interoperability, the ability for AI agents to communicate and collaborate across different platforms, will mark the end of the era of fragmented automation. For enterprises, this translates to streamlined workflows, faster decision cycles, and fewer operational bottlenecks across the value chain. For instance, in manufacturing, AI will autonomously manage production, expedite lots, optimise inventory, schedule operations, and reallocate capacity, thereby driving lower costs, higher throughput, and greater resilience. In sectors like retail, AI will move beyond efficiency to create value, turning loyalty programmes into personalised experience ecosystems that influence demand and support premium pricing.

Open-source models will enable Indian enterprises to build sector-specific AI, enhancing insights, speed, and differentiation. Self-verifying agents and natural-language programming will reduce oversight and simplify workflows. Lean, specialised models will enable AI quality control, with proprietary data powering “data flywheels” that enhance performance.

Cybersecurity will also transform. AI will provide defenders with the scale to triage threats, detect anomalies, and strengthen enterprise resilience over the next few years.

Roadblocks in the path to success

According to Ecosystm, 77% of organisations struggle to demonstrate a measurable RoI, 67% face challenges with legacy systems, and 66% are hindered by regulatory complexities. Unlocking AI’s full potential will require unified data foundations, strong governance, and tight collaboration between AI systems and human expertise. Ultimately, the real limit to AI decision-making won’t be the model's capability, but the depth and quality of an organisation’s data. It’s well known that AI models are only as good as the data they are trained on, and because of this, data has become every businesses’ most valuable asset. Enterprises require real-time access to high-quality data to achieve success. They need to invest in a cloud-based, scalable, integrated data platform that supports their business growth and expansion.

The road ahead

In this new AI era, traditional roles will also undergo evolutionary growth. Some roles will fade, new ones will emerge, and nearly all will require AI-aligned skills. Every employee will need to upskill or reskill as AI becomes part of daily work, making AI skilling a core strategic priority. By 2026, companies will need dedicated AI change-management teams to drive reskilling, build trust, redesign incentives, and reshape workflows. AI adoption is not just a tech upgrade; it is a cultural shift. Employees must know when to trust AI and when to override it. Therefore, organisations that succeed will be those that treat AI as a system that transforms decision-making and accountability throughout the business. The leaders who succeed will not just invest in more powerful AI. They will invest in the people and processes that turn data into insights and a reliable, shared reality - and only then unlock the true potential of AI at scale.

(The author is MD, India, Snowflake. Views are personal)