At AeraHUB 25 in New York City, IDC’s Megha Kumar unveiled new global research that captures a pivotal moment in enterprise transformation. The whitepaper, Accelerating Enterprise Decision Intelligence with AI Agents, sponsored by Aera Technology, explores how organizations are evolving from AI-assisted insights to AI-agent-enabled action, reshaping how they think, decide, and operate.

Two years after IDC and Aera’s earlier study, What Every Executive Needs to Know About AI-Powered Decision Intelligence, this new research shows just how far organizations have come. What began as experimentation has become enterprise-wide integration. IDC now forecasts that global AI spending will reach $1.3 trillion by 2029, with Generative AI accounting for more than half. Yet even as AI becomes pervasive, a persistent gap remains between insight and execution — a divide that AI agents are uniquely positioned to close.

The New Frontier: From Insight to Action

That transition from insight to execution defines the next phase of enterprise evolution. IDC describes AI agents as software that “perceives, makes decisions, and acts on those decisions by combining insights from large language models with the ability to execute through tools and data sources.” In other words, where traditional AI systems inform, agents act — within set boundaries and often alongside human oversight.

For early adopters, this shift is already paying off. A global manufacturer used AI agents to optimize production and distribution, improving fulfillment speed and inventory balance. Others are automating thousands of planning decisions each month, enabling faster response times without sacrificing human judgment. Together, these examples illustrate a powerful trajectory: organizations are moving from insight generation to intelligent execution, where technology and people collaborate continuously to drive performance.

Defining the Six Competencies of Decision Intelligence

To better understand how enterprises are advancing along this path, IDC surveyed 311 large organizations across 11 countries and six industries. The goal: to explore how AI is being applied across six key decision-making competencies: data acquisition, analysis, simulation, collaboration, execution, and monitoring and learning.

When these competencies operate in isolation, decisions remain fragmented and slow. But when connected in a closed loop, they form a self-reinforcing system that enables continuous learning, faster action, and greater consistency. That’s why 40% of surveyed organizations said they are adopting decision intelligence to address inefficiencies and rising costs while improving agility.

The research also found common priorities across respondents:

• Ensuring access to decision intelligence platforms
• Empowering employees with AI agents to make faster, policy-aligned choices
• Automating operational decisions where appropriate
• Standardizing decision processes across functions

As enterprises connect these competencies and adopt AI agents, they’re not just improving decision-making; they’re fundamentally redesigning how decisions happen, shifting from periodic reviews to continuous, adaptive cycles of action and learning.

The State of Decision-Making Today

Even so, many organizations remain in transition. IDC’s findings reveal that most still rely on a mix of human experience, data insights, and AI-generated recommendations. Only about 10% base decisions primarily on AI, and a vast majority continue to use disconnected tools — 87% rely on spreadsheets, alongside various BI, data governance, and planning systems.

This fragmentation creates friction. Insights are generated faster than they can be acted upon, and valuable lessons often remain siloed within teams. Without integrated feedback loops, decision outcomes aren’t consistently measured or applied to future scenarios. Over time, this weakens institutional memory and erodes the ability to improve decision quality.

The message is clear: to move from informed to intelligent decision-making, organizations need a unified platform that embeds AI directly into the decision process, connecting insight, execution, and learning into one continuous flow.

The Rise of AI Agents and Unified Platforms

That unified approach is quickly gaining traction. IDC’s study found that 88% of surveyed organizations have implemented or plan to pilot decision intelligence initiatives, and nearly 60% see strong value in a single platform connecting all six decision-making competencies.

AI agents sit at the center of this evolution. Two in five respondents identified agents as the key technology enabling advanced decision intelligence. Most expect AI agents to significantly enhance four of the six competencies — data acquisition, analysis, simulation, and monitoring — paving the way for continuous, self-improving decision cycles.

Trust, however, remains essential. Roughly one-third of organizations say AI agents should assist without decision authority, while another 30% prefer that all actions be human-approved. Over the next two years, this balance will begin to shift, with many enterprises allowing agents to manage routine, low-risk decisions under human oversight. The result will be a hybrid model in which people and AI agents collaborate seamlessly, combining speed and scale with transparency and control.

What Sets Decision Intelligence Leaders Apart

As the study makes clear, not all organizations are progressing at the same pace. IDC segmented respondents into groups based on how connected and automated their decision processes are. Decision intelligence leaders, those that have integrated most or all six competencies, stand well ahead of their peers.

Among these leaders:

• 58% use AI to support business decision-making
• 72% have deployed decision intelligence in one or more functions
• 74% view unified platforms as highly beneficial

These organizations outperform decision intelligence followers by an average of 40 percentage points across key benefits such as decision speed, consistency, and governance. They also report higher customer satisfaction (78% vs. 61%) and improved operational efficiency (75% vs. 41%). The difference isn’t simply technological; it’s structural and cultural. By closing the loop between data, action, and learning, leaders are turning decision-making into a measurable, strategic advantage.

Guidance for the Path Ahead

IDC’s research also highlights several practical steps for organizations aiming to advance their decision intelligence maturity and realize the full potential of AI agents:

1. Start with high-impact use cases. Focus on areas where decisions are frequent, data-rich, and measurable (such as supply chain, pricing, finance, or operations) to demonstrate early success and build confidence.
2. Automate routine decisions. Target repetitive, low-risk activities to free up human capacity for higher-value collaboration and innovation.
3. Invest in a unified platform. Connect data, analytics, simulation, execution, and learning in one environment to ensure that intelligence flows seamlessly from insight to action.
4. Maintain human oversight. Balance automation with transparency through explainable models, clear governance, and human-in-the-loop controls.
5. Build AI and data literacy. Empower employees to understand, interpret, and challenge AI-driven insights, strengthening trust and accountability across the enterprise.

By combining technology investment with governance and education, organizations can accelerate adoption while maintaining alignment between automation, oversight, and strategic intent.

A Defining Shift Toward Agentic AI

As Megha Kumar emphasized at AeraHUB 25, decision intelligence is no longer a concept reserved for innovators — it’s a strategic necessity for every enterprise navigating complexity and change. The organizations that integrate AI agents into their decision frameworks will not only act faster but also learn faster, adapt sooner, and compete smarter.

For full details on IDC’s global research and its findings on how AI agents are transforming enterprise decision-making, download the whitepaper: Accelerating Enterprise Decision Intelligence with AI Agents.