Security consolidation shifts enterprise spending towards AI governance, email security and insider risk: Proofpoint

The shift is expanding advisory opportunities for MSSPs and channel partners as customers seek help governing AI adoption, securing human risk and simplifying complex cyber environments.

Enterprises are simplifying cybersecurity environments as AI introduces new attack surfaces, governance challenges and operational complexity that existing security architectures were never designed to manage.

“The shift is changing both enterprise buying priorities and partner opportunities. As organisations operationalise AI across business functions, customers are looking beyond traditional threat prevention towards technologies that provide visibility into AI applications, behavioural analysis, governance controls and operational resilience,” Proofpoint India country manager Bikramdeep Singh told CRN India.

According to Singh, security consolidation has been underway for several years, but AI is accelerating the need to simplify enterprise security environments.

He said organisations managing products from large numbers of security vendors face growing operational complexity as new AI models introduce additional vulnerabilities and increase the burden of patching and maintaining disparate technologies.

"The more security tools an organisation has, the more vulnerabilities and patches it has to manage," Singh said.

Instead of continuing to expand their security estates, enterprises are standardising around a smaller number of strategic security pillars covering network infrastructure, security operations, identity, insider threat management and secure gateways.

Email security continues to remain one of the most critical components of that strategy because it remains one of the primary entry points for social engineering attacks.

At the same time, organisations are shifting from rule-based detection towards behavioural analysis, focusing on whether users are performing activities that differ from their normal patterns rather than relying solely on predefined alerts.

According to Singh, forensic capabilities are becoming equally important as organisations seek greater operational visibility across complex AI-enabled environments.

AI security becomes the next investment priority

Beyond consolidation, Singh expects enterprises to increase spending on technologies that secure AI adoption itself.

He described AI security as extending well beyond using artificial intelligence to improve threat detection.

Instead, organisations require visibility into every AI application operating across the enterprise, whether officially approved or introduced independently by employees.

They also need assurance that AI systems access only authorised enterprise data while maintaining forensic records that allow security teams to investigate AI-related activity when required.

"For us, AI security is not just about using AI to improve threat detection. It is also about securing the use of AI itself," Singh said.

Singh also identified insider threat protection as an important investment area as organisations deploy larger numbers of AI agents capable of accessing corporate information and interacting across multiple enterprise systems.

Alongside these priorities, he expects enterprises to invest more heavily in AI infrastructure, including AI-ready data centres, over the next 12 to 18 months.

MSSPs move from technology providers to AI advisors

Those changing customer priorities are also reshaping the role of managed security service providers.

According to Singh, keeping pace with rapid innovation across multiple cybersecurity platforms remains challenging for MSSPs, particularly as customers expect immediate access to new capabilities without disrupting existing security operations.

Rather than fundamentally changing how services are delivered, Singh said vendors need to help partners introduce new AI security capabilities with minimal operational disruption.

At the same time, he believes customer engagement is becoming significantly more consultative.

Instead of focusing primarily on technology deployment, MSSPs need to understand how customers are adopting AI, evaluate insider risk, assess data exposure and recommend governance controls that align with business objectives.

"The relationship is becoming much more consultative and engagement-driven," Singh said.

According to him, the opportunity depends on how effectively partners help organisations balance AI adoption with appropriate security and governance.

Third-party resilience becomes part of enterprise security strategy

The growing complexity of enterprise ecosystems is also changing how organisations approach cyber resilience.

According to Singh, third-party relationships have always represented a significant source of operational risk, but enterprises, particularly in the BFSI sector, are now imposing far stricter cybersecurity requirements on technology suppliers before allowing them to deliver services.

That has increased demand for practices such as network segmentation, vendor risk assessments and third-party security assessments to better understand the security posture of external partners.

Although organisations rarely expose critical application infrastructure directly, interactions between connected systems continue to increase, making supplier security capabilities an important component of enterprise cyber resilience.

Singh said the change is encouraging technology vendors themselves to invest more heavily in cybersecurity as they seek to meet the security expectations of large financial institutions and remain part of interconnected enterprise ecosystems.

For channel partners, the transition extends the opportunity beyond deploying security products towards helping customers simplify complex security environments, govern AI adoption and strengthen resilience across interconnected digital supply chains.