AI is beginning to redraw the lines between high-value IT services and work that is increasingly vulnerable to automation.
Michael Rosholt, senior vice president at M&A advisory firm martinwolf, says buyers are looking beyond AI messaging to determine whether technology is actually improving margins, delivery and profitability, while favoring services where complexity, strategic guidance and human expertise remain difficult to automate.
Channel Insider spoke with Rosholt about how those shifts are affecting IT services valuations, implementation businesses, and cybersecurity providers, as well as the opportunities channel partners should prioritize as AI adoption accelerates.
AI is changing how buyers value IT services
Is AI creating clear winners and losers across the IT services market?
While it is still too early to say definitively who the long-term winners and losers will be, in the verticals we cover we see a wide gap between companies that are being directly threatened by AI and those that have moved ahead of the curve by using it to improve delivery, margins, and growth.
In the short term, the companies best positioned today are proactively incorporating AI into their operating models in ways that strengthen profitability and customer value.
How should potential buyers evaluate whether an IT services business is truly benefiting from AI and not simply using it as a marketing message?
There is no shortage of companies using hyperbolic AI language today, so buyers must look for evidence that AI is actually improving the business.
That means asking for specific data on how AI is helping the company improve metrics such as time spent on billable work vs. administrative tasks, delivery speed, margins, overhead costs, or the volume of customers supported.
The strongest companies will be able to show prospective buyers measurable operational impact and a clear connection to AI adoption and profitability.
Which IT verticals are seeing the strongest growth as AI adoption accelerates?
The verticals that jump to mind are identity and access management, data analytics and engineering, digital transformation consulting, enterprise knowledge management, and solution providers specializing in data center buildouts or management.
These verticals are benefiting because widespread AI adoption increases the need for secure access, better data infrastructure, more sophisticated transformation strategies, and expanded computing capacity.
How is AI affecting software companies and software valuation trends?
Software companies are seeing major shifts in valuation due to AI, and this is impacting M&A. In some cases, sale processes have been paused or canceled because valuation expectations have changed significantly over the last 12 months.
Buyers are paying closer attention to whether a software company has durable earnings, a stable customer base, disciplined cost allocation, and a clear ability to generate free cash flow.
Even so, AI is not purely a negative force on the valuations of software companies. While it can pressure valuations by making some intellectual property and development work easier to replicate, it can also help software businesses reduce overhead, improve margins, and increase profitability.
Fast-growing, profitable software companies that can demonstrate a credible path toward further margin expansion through AI-enabled engineering or development workflows are maintaining healthy valuations and attracting strong buyer interest.
Complex IT services remain harder for AI to disrupt
Are implementation-focused services businesses being helped or hurt by AI?
The impact of AI depends heavily on the complexity of the implementation. For example, within the Microsoft Dynamics ecosystem, Business Central is typically used by small and midsize businesses or organizations with more straightforward operations, and AI hasn’t been much of a disruptor.
The ecosystem remains healthy because the work still requires product knowledge, business process understanding, and customer-specific execution.
AI has had a positive effect on more complex finance- or operations-focused ERP implementations because large, complex organizations still require significant human problem-solving.
AI can assist in the background, but the rate of billable client-facing work remains high because these projects involve operational complexity, change management, and judgment that cannot be fully automated.
On the other hand, CRM implementations are often more standardized and involve more straightforward customization. In those cases, AI can enable engineers and representatives to support more clients but can also reduce billable utilization unless the business grows fast enough to offset the shift.
READ MORE: OSF Digital is focused on bringing AI advisory services to the Salesforce ecosystem.
What is happening across cybersecurity and ransomware incident response?
These have historically been discussed together, but AI adoption is causing the two areas to diverge. With cybersecurity, AI is helping move platforms from rule-based systems toward technologies that can detect unusual network behavior in real time, identify malware and phishing attempts faster, automate threat detection and incident response, and predict vulnerabilities before they can be exploited.
Firms that implement or consult on leading AI-enabled cybersecurity technologies are meaningfully benefiting from this shift.
Ransomware incident response, on the other hand, is seeing a different impact. While it has historically seen strong growth and buyer interest, as cybersecurity technologies improve, the number of incidents requiring traditional response services may decline.
This trend can leave some ransomware-focused businesses on the wrong side of the AI adoption curve, particularly if their growth model depends on a high volume of incidents rather than proactive prevention or broader security services.
What about IT asset disposal and IT asset management firms?
IT asset disposal (ITAD) and IT asset management (ITAM) firms are seeing significant growth because AI adoption requires more data center capacity, computing power, and hardware investment.
As companies spend more on infrastructure, they also need sophisticated providers that can help recover value from old equipment, ensure devices are properly wiped and cleaned, and dispose of hardware in an environmentally responsible manner.
That makes ITAD and ITAM providers increasingly important parts of the broader AI infrastructure ecosystem poised for continued growth.
Channel partners need to move toward higher-value expertise
What should channel partners do now to avoid being disrupted by AI?
Develop capabilities that AI makes more important. That includes advisory services, complex implementation expertise, cybersecurity consulting, data strategy, infrastructure planning, and managed services that help customers apply AI responsibly and effectively.
Partners that rely only on straightforward technical execution may face utilization pressure, while those that can combine automation with strategic guidance into a value-added offering will be better positioned to protect client relationships and expand their role in the customer journey.
READ MORE: Some MSPs and other partners are already developing the next evolution of services-led offerings.
Where are customers most likely to keep relying on human expertise despite rapid AI adoption?
Areas where business context, judgment, and risk management matter as much as technical execution. Complex ERP implementations, cybersecurity strategy, data architecture, digital transformation, and infrastructure planning all require teams that can interpret customer needs, manage change, and solve problems that do not fit neatly into a repeatable workflow.
AI can assist with execution, but the human role remains critical when decisions affect operations, compliance, security, and long-term business outcomes.
The AI winners will combine automation with specialized expertise
Any final thoughts?
The biggest winners today appear to be implementation businesses where complexity still requires human problem-solving: IT asset disposal and IT asset management providers, and cybersecurity businesses delivering AI-enabled prevention, detection, and response.
The businesses facing the most pressure include certain software companies, ransomware response providers, and implementation firms focused on simpler integrations where AI can reduce the need for manual work.
Ultimately, the market is likely to reward companies that use AI to improve efficiency while still providing specialized expertise, strategic guidance, and services that remain difficult to automate.