Tech stocks go into free fall as it dawns on traders that AI has the ability to cut revenues across the board
What it means for consulting firms like Deloitte, PwC & CGI ?
1) “Seat compression” likely leads to “project compression.”
If AI agents let one person do the work of many, companies will try to run leaner teams and reduce the number of people who need to touch systems day-to-day. For consulting, that usually means:
Less billable work at the junior/repetitive level: basic configuration, documentation, manual testing, and simple reporting/dashboards. In Salesforce specifically, some of that is already partly “templated” (e.g., template dashboards) so clients will question paying extra for work that feels standardized.
Faster timelines—sometimes. Clients will be less patient with long delivery cycles if AI genuinely speeds up delivery. In practice, this acceleration tends to show up only when AI capability is actually deployed and adopted (e.g., “only if and when Agentforce is implemented,” and the client has the data, governance, and operating model to use it).
2) The value moves up-market: operating model, governance, integration—and privacy/security.
Even if AI reduces some build effort, it increases demand for the work that’s difficult to automate and high-risk if done wrong. This is where consulting shifts from “building screens” to “running the business safely with AI,” including:
Data readiness: getting customer and operational data clean, consistent, and usable across teams
Governance for AI/agents: clear approvals, accountability, audit trails, and controls so automated actions don’t create business risk
Security, privacy, and compliance: stronger guardrails, including data privacy, security, encryption at rest, and ongoing AI monitoring
Integration: connecting CRM to finance, service, ERP, identity systems, and data platforms so AI can work across the full process
Change management: retraining teams and redefining roles when “agents do the work”.
This is why many consulting firms are publishing responsible-AI and “agent workflow” playbooks: they see this as an enduring line of business, not a temporary trend.
3) Pricing pressure: time-and-materials gets squeezed.
If clients believe AI should make delivery faster and cheaper, they’ll push for:
Fixed-fee or outcome-based pricing (pay for results, not hours)
Managed services where automation is built into standard operating procedures
Reusable assets (templates, accelerators, proprietary toolkits) to lower cost and protect margins
Big firms often do well here—if they pivot quickly—because they can standardize delivery at scale. Smaller boutiques can also win by being more AI-native and cost-competitive.
4) How this plays out by firm
Deloitte / PwC: likely to double down on being the “safe hands” for AI adoption—governance, regulated industry transformation, assurance, and risk management—rather than relying on pure configuration hours.
CGI: often strongest in public sector and long-term managed services. AI can improve margins by automating operations, but it can also create contract risk if revenue is tied to staffing volume.
That said, CGI can evolve into a stronger “AI readiness” and risk/governance consulting partner—more like the Deloitte/PwC positioning—by building deeper offerings in governance, regulated transformation, and assurance.
Context note on origins: Deloitte and PwC historically grew their influence through business consulting and expanded into tech/implementation ecosystems, including SaaS. CGI can pursue new revenue streams by moving further up the value chain (governance + regulated transformation + assurance), reducing dependence on commodity implementation hours.
Net effect for consulting:
Expect margin pressure on commoditized “SaaS delivery” work, but growth in higher-value advisory and “AI operations” services. The winners will shift from selling hours to selling outcomes and reusable assets.
CGI opportunity:
“Deloitte and PwC captured a lot of the value in SaaS consulting. Now AI opens the door to capture more of the value in business consulting—for IT players like CGI because clients need guidance, control, and accountability, not just configuration.”
Plain business translation: As AI makes parts of implementation faster and more standardized, clients will spend less on routine build work and more on higher-value decisions: what to automate, how to manage risk, how to protect data, how to measure results, and how to redesign processes and roles. The firms that win will be the ones who can tie AI adoption to clear outcomes, strong governance, and sustainable operating models—not just deliver more configuration hours.
