Authored by Novus Insights
29/06/2026
Artificial intelligence is entering a new phase of enterprise adoption with the rise of Agentic AI. Unlike traditional AI systems that primarily respond to prompts, agentic AI can autonomously make decisions, execute tasks, interact with multiple systems, and pursue predefined objectives with minimal human intervention, enabling businesses to automate complex workflows and improve operational efficiency at scale.
However, the race toward automation is not without risk. Organizations must carefully evaluate technological, operational, governance, cybersecurity, and compliance challenges before deploying autonomous AI systems at scale. In this article, we discuss how market research becomes critical in helping businesses identify opportunities, benchmark adoption strategies, assess risks, and make informed investment decisions.
Organizations are increasingly viewing agentic AI as the next major leap in enterprise automation. The opportunity is substantial. According to a McKinsey article, agentic AI systems could help unlock between $2.6 trillion and $4.4 trillion in annual value across more than 60 generative AI use cases, including customer service, software development, supply chain optimization, and compliance functions.
Key drivers include:
The momentum behind adoption is significant. According to a Deloitte report, surveying 3,235 business and technology decision-makers across 24 countries spanning the Americas, Europe, Asia Pacific, and the Middle East, 74% of organizations expect to use AI agents at least moderately by 2027.
Similarly, NVIDIA's State of AI Report found that 44% of surveyed organizations were either actively deploying or evaluating AI agents during the survey period, highlighting strong enterprise interest even in the early stages of adoption.
These figures highlight growing confidence in agentic AI's potential to reshape enterprise processes and competitive advantage.
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Although adoption remains in the early stages, several industries are already experimenting with agentic AI.
1. IT Operations
Agentic systems are being used to monitor infrastructure, detect anomalies, automate incident management, and support software development workflows.
2. Telecommunications
Telecom providers are exploring autonomous network optimisation, predictive maintenance, customer support automation, and service assurance applications. This trend is creating growing demand for telecom market research and telecom industry market research to evaluate adoption readiness and operational impact.
3. Cybersecurity
Security teams are deploying AI agents to identify threats, automate investigations, prioritise alerts, and coordinate incident response.
4. Supply Chain Management
Businesses are using agentic AI to optimise procurement, inventory management, logistics planning, and demand forecasting.
5. Customer Service
AI agents can manage customer interactions, resolve routine issues, and escalate complex cases to human representatives when necessary.
Despite its potential, agentic AI introduces a new category of enterprise risks.
AI systems remain imperfect. They can generate inaccurate outputs, misinterpret instructions, or make decisions based on incomplete information.
Agentic AI often interacts with multiple applications and databases simultaneously. Errors within one system can quickly cascade across connected workflows.
Incorrect decisions made autonomously can result in financial losses, reputational damage, customer dissatisfaction, or regulatory violations.
Synthetic identities are AI-generated or manipulated digital identities that can be used to bypass verification systems and facilitate fraud. Bad actors may use AI-generated identities to bypass security controls, commit fraud, or manipulate automated workflows.
Autonomous systems frequently require access to sensitive corporate data. Poor governance can expose organizations to data leakage and privacy violations.
AI agents themselves can become targets for manipulation, adversarial attacks, credential theft, or malicious prompt injection attempts.
Agentic AI systems may inadvertently violate regulations such as GDPR, the Equal Credit Opportunity Act (ECOA), or industry-specific compliance requirements if proper controls are not established.
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Before deploying agentic AI systems, organizations should evaluate several critical questions:
Addressing these questions early can significantly reduce implementation risks.
Deloitte's research highlights a major challenge facing enterprises today. While AI agent adoption is accelerating, approximately 80% of surveyed organizations currently lack mature governance capabilities for agentic AI, including clear decision boundaries and human oversight frameworks.
Without proper governance, organizations risk creating autonomous systems that operate without sufficient accountability, transparency, or control.
A successful governance framework should include:
1. Establish Robust Policy Frameworks
Develop clear policies governing AI usage, decision authority, accountability, and escalation procedures.
2. Strengthen Identity and Access Management (IAM)
Ensure agents only access systems and data required for their specific functions.
3. Implement Third-Party Risk Management (TPRM)
Evaluate risks associated with external AI models, vendors, APIs, and software providers.
4. Align with Regulatory Requirements
Maintain compliance with GDPR, ECOA, and other applicable legal frameworks.
5. Adopt Established Cybersecurity Standards
Organizations should align with recognised frameworks such as:
6. Create Human Override Mechanisms
Every autonomous system should include contingency plans, escalation pathways, and manual intervention capabilities.
Successful agentic AI implementation requires more than technology investments. Organizations must understand market dynamics, adoption patterns, competitive activity, and risk exposure before deployment.
This is where market research becomes a strategic advantage.
Market research helps organizations evaluate technology maturity, workforce preparedness, infrastructure readiness, and operational suitability for agentic AI deployment.
Not every process should be automated. Research helps prioritize use cases with the greatest potential return on investment.
Understanding how peers and competitors are adopting agentic AI enables businesses to make more informed strategic decisions.
Research frameworks can identify operational, regulatory, cybersecurity, and organizational risks before deployment begins.
Pilot testing, stakeholder interviews, and feasibility studies help organizations refine implementation approaches before committing significant resources.
Organizations typically use a combination of executive interviews, stakeholder surveys, competitor benchmarking, technology landscape analysis, customer research, feasibility studies, and risk assessments to evaluate agentic AI opportunities.
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The IT and telecommunications sectors are expected to be among the largest adopters of agentic AI technologies.
Through comprehensive IT industry analysis with Novus Insights, organizations can evaluate:
Similarly, telecom industry market research helps service providers assess:
Businesses increasingly rely on IT industry and telecom market research consultants to guide AI investment strategies and reduce implementation uncertainty.
As adoption accelerates, demand for experienced IT market research companies is expected to grow significantly.
According to BCG, agentic AI could generate up to $200 billion in new value pools globally over the next five years, significantly expanding the technology services market. This projected growth reflects the increasing role of autonomous AI systems across enterprise operations, suggesting that the future of agentic AI extends far beyond isolated automation projects.
Emerging developments include:
At the same time, regulatory oversight is expected to increase substantially. Organizations that establish strong governance structures today will be better positioned to capture future opportunities while minimizing risk.
The challenge is no longer whether agentic AI will be adopted. The challenge is determining how to deploy it responsibly, securely, and strategically.
As enterprises move from experimentation to implementation, access to reliable market intelligence becomes increasingly important. Understanding adoption trends, competitive activity, customer expectations, and regulatory developments can significantly improve deployment outcomes.
Navigating the opportunities and risks associated with agentic AI requires a clear understanding of market dynamics, competitive activity, technology readiness, and enterprise adoption trends.
At Novus Insights, we bring over two decades of experience in market research consulting, helping organisations make informed business decisions through data-driven analysis and customised research solutions. Whether you require IT industry analysis, telecom market research, adoption feasibility assessments, competitive benchmarking, or risk evaluation studies, our team can help you identify opportunities and reduce uncertainty.
To learn more about how we can support your business, contact us at +91 124-436-6686, +91 7428 225 350, or email contactus@novusinsights.com. You may also fill out our contact form, and one of our representatives will get in touch with you shortly.
Q.1 What is agentic AI, and why is it important for businesses?
Agentic AI refers to AI systems capable of autonomously making decisions and executing tasks to achieve specific goals. As organisations explore new automation opportunities, agentic AI is becoming a key focus area in IT industry analysis due to its potential to improve productivity, operational efficiency, and decision-making.
Q.2 How can market research support agentic AI adoption?
Market research helps organizations evaluate technology readiness, identify high-impact use cases, benchmark competitors, and assess implementation risks. At Novus Insights, we combine industry expertise with data-driven methodologies to help businesses make informed AI investment decisions.
Q.3 Why is IT industry market research important before implementing agentic AI?
IT industry market research provides valuable insights into adoption trends, emerging technologies, customer expectations, and competitive activity. These insights help organizations prioritize AI initiatives, reduce uncertainty, and align investments with business objectives.
Q.4 How does telecom market research help telecom operators adopt agentic AI?
Telecom market research enables service providers to evaluate opportunities in network automation, customer service optimisation, predictive maintenance, and operational efficiency. It also helps identify potential risks, investment priorities, and evolving customer requirements before large-scale deployment.
Q.5 What role do telecom market research consultants play in AI strategy development?
Telecom market research consultants provide industry-specific intelligence, competitive benchmarking, and feasibility assessments to support strategic decision-making. Their insights help telecom operators develop practical AI adoption roadmaps while addressing regulatory, operational, and technology-related challenges.
Q.6 How can telecom industry market research reduce the risks associated with agentic AI?
Telecom industry market research helps organisations understand market dynamics, customer expectations, infrastructure readiness, and cybersecurity concerns. By identifying potential challenges early, businesses can develop stronger governance frameworks and minimize deployment risks.
Q.7 Why are telecom market research reports valuable for technology and business leaders?
Telecom market research reports provide structured insights into industry trends, emerging technologies, customer behavior, competitive developments, and investment opportunities. These reports help executives make more confident decisions regarding AI adoption, digital transformation, and long-term growth strategies.
Q.8 How can IT market research companies help organisations evaluate agentic AI opportunities?
Experienced IT market research companies help businesses assess technology maturity, benchmark competitors, identify high-value use cases, and quantify potential risks and returns. At Novus Insights, we support organizations with customized research solutions that enable smarter and more strategic AI adoption decisions.