In the cyber-threat landscape, adversaries are increasingly using artificial intelligence (AI) not just defensively but aggressively. Attackers aren’t guessing; they’re automating. They can write convincing phishing emails, mimic real voices, and find vulnerabilities instantly. It’s efficient and relentless. 

That development has powerful implications for managed service providers (MSPs) and their clients. MSPs must both defend against AI-enabled attacks and adapt their contracting, liability models, and service delivery to survive this new era.

1. Specific Threat Examples

Cybercriminals no longer rely solely on human-crafted phishing templates or manual threat hunts. They’re now using AI to magnify and automate operations. For example:

• Generative-AI models are being used to craft extremely plausible spear-phishing and deep-fake social engineering campaigns — exploiting voice, image and text mimicry to trick users. A recent report found that 63% of 3,000 IT/cyber pros flagged AI-driven social engineering as a major challenge in 2026.¹
• Autonomous reconnaissance and kill-chain prediction tools are being developed that can identify likely victim systems in real time, map out an attack path, and execute lateral moves with minimal human oversight.²
• Surveys show 63% of C-suite executives believe AI-enhanced threats could render existing defences obsolete every few months, more than double from the previous year.³
  For MSPs this means the attack surface is changing: it’s faster, smarter, more scalable and more automated. Traditional perimeter-based defences or static signature-driven tools are no longer sufficient.

2. Practical Strategies for MSPs

To stay ahead, MSPs need to flip from purely reactive to proactive models:

• Integrate AI-capable defensive tools (for example, anomaly-detection, behavioral modelling) and maintain human expert oversight — AI isn’t a substitute for expertise, but a force-multiplier.
• Move toward layered, adaptive controls: Zero-Trust architectures, multi-factor authentication (MFA) for all clients, and continuous monitoring of unusual patterns (especially around privileged accounts and API usage).
• Build the service model to include AI-readiness consulting: Many clients may deploy generative-AI or large-language models (LLMs) but lack the security maturity — MSPs can position themselves as advisors to fill that gap.
• Develop incident-response and playbook templates oriented around AI-enabled threats: faster detection, automation of triage, clear escalation paths when AI triggers human review.

3. Contracting, Liability & Insurance Implications

With this shift, MSPs must revisit how they contract with clients and manage risk:

• Service Level Agreements (SLAs) and Master Services Agreements (MSAs) must explicitly address scenarios where AI-based threats create novel exposures. Which party is liable if an attack is triggered by AI-generated content (e.g., deep-fake impersonation) and how will response responsibilities be allocated?
• Cyber-liability insurance policies may need updates. Insurers increasingly expect evidence of AI-capable defence tools, regular red-teaming of AI vectors, and documented oversight of AI workflows.
• MSPs should include audit rights, responsibilities for AI tool maintenance, training requirements (for client staff and MSP staff on AI-related threats) and clear indemnity language around “known unknowns” of AI exploitation.
• From a client-advisory perspective, MSPs should include security-by-design for AI use-cases (if the client is deploying AI themselves) and ensure proper data governance, model validation and human-in-the-loop controls.

4. Case Study / Vendor Move

A recent example: Kaseya’s acquisition of INKY (announced 7 Oct 2025) exemplifies how MSP-focused vendors are embedding AI into their platforms. INKY brings generative-AI-based email security — enabling MSPs to defend against highly sophisticated phishing and impersonation vectors.⁴

This move shows both the demand for AI-driven security within the MSP ecosystem and how platform vendors are adapting. For MSPs this means:

• Expect consolidation and deeper tool-integration: single dashboards that combine email, identity, endpoint, backup, and AI-analytics.
• Need to evaluate vendor AI-claims carefully (look for transparency around data sets, false-positive rates, human-oversight).
• Opportunity to differentiate by offering “AI-enhanced defense” as a premium service tier: clients will pay more for higher confidence in the face of AI-enabled threats.

Final Thoughts

So where does this leave MSPs? In short, right in the middle of a massive shift — and a big opportunity.

The same AI that fuels cybercrime can also become your best defensive tool. 

But that requires more than new software; it takes smarter contracts, sharper oversight, and steady human judgment. By proactively embracing this shift, MSPs can position themselves as strategic, rather than just operational, partners to their clients.

MSPs that lean into AI — thoughtfully, transparently, and strategically — will set the new standard for cybersecurity in 2026 and beyond.

Footnotes

1. “AI-Driven Social Engineering Top Cyber Threat for 2026, ISACA Survey Reveals”, Infosecurity Magazine. (infosecurity-magazine.com)
2. “Cyber Threat Intelligence: AI-Driven Kill Chain Prediction”, Cloud Security Alliance. (cloudsecurityalliance.org)
3. “Will AI Cyber Threats Outpace AI Defenses?”, Forbes. (forbes.com)
4. “Kaseya expands backup portfolio, acquires email security specialist INKY”, IT Pro. (itpro.com)