FTI Consulting’s Q2 2026 Results Highlight Resilience Amid Rising Costs

Software Lifecycle Engineering

FTI Consulting posted record Q2 2026 revenues of $993.5 million, up 5.3% year-over-year [1], as enterprises accelerate technology transformation investments requiring expert advisory support. The Software Lifecycle Engineering market underpinning this demand is forecast to reach approximately $271.3 billion in 2026 and $344.0 billion by 2028, at a 15.4% CAGR from 2023 to 2028 [2]. Persistent AI governance gaps, including only 45.1% of organizations (out of 839 surveyed) maintaining audit logging for AI agent actions [3], are creating durable consulting opportunities for firms positioned at the intersection of technology capability and risk management.

What is Covered in this Article

  • FTI Consulting Q2 2026 record revenue performance [1]
  • Software Lifecycle Engineering market growth trajectory [2]
  • Enterprise AI adoption in development workflows [4]
  • AI governance gaps driving advisory demand [3][3]
  • SLE investment intentions among decision-makers [3]

The News: FTI Consulting reported record Q2 2026 revenues of $993.5 million, an increase of $49.8 million or 5.3% compared to $943.7 million in the prior year quarter [1]. The result reflects sustained enterprise demand for advisory services as organizations work through accelerating technology transformation. This momentum aligns with a broader market shift: the Software Lifecycle Engineering market is projected to reach approximately $271.3 billion in 2026 and $344.0 billion by 2028, compounding at a 15.4% CAGR from 2023 to 2028 [2], driven by enterprise adoption of AI-assisted development, agentic tooling, and platform engineering. With a majority of surveyed organizations already using AI technologies in development workflows, including AI code completion or generation, AI test development, and AI agents and copilots [4], the advisory opportunity for firms like FTI is both immediate and expanding.

FTI Consulting's Record Quarter Signals Growing Enterprise Demand for AI Advisory

Analyst Take: FTI Consulting's record quarter is not an isolated data point, it reflects a structural shift in enterprise spending toward technology advisory as AI reshapes software development at scale [1]. The SLE market's projected growth to approximately $344.0 billion by 2028 at a 15.4% CAGR [2] creates a large and durable addressable market for consulting firms that can translate AI capability into operational and governance outcomes. The critical question is whether FTI can capture a disproportionate share of this demand as enterprise buying decisions grow more complex.

A Market on a Steep Growth Curve

The SLE market is forecast to reach approximately $271.3 billion in 2026 and $344.0 billion by 2028, compounding at a 15.4% CAGR from 2023 to 2028 [2]. This trajectory is being driven by enterprise adoption of AI-assisted development, agentic workflows, and platform engineering practices. Notably, surveyed organizations are already using AI technologies in development, spanning AI code completion or generation, AI test development, and AI agents and copilots [4]. However, adoption is uneven. Some 47.2% of organizations remain at the individual developer assistance stage, using IDE completion and chat tools [3], while more sophisticated agentic deployments are still emerging. This maturity gap is precisely where advisory firms find their most durable engagements: helping enterprises move from point-tool adoption to integrated, governed AI development platforms.

Investment Intent Is Real, But Governance Is Lagging

Budget signals from SLE decision-makers are constructive. Among 839 surveyed decision-makers, 45.6% plan to slightly increase investment in the 5 to 15% range over the next 12 months [3], indicating continued expansion rather than consolidation. Yet the governance infrastructure to support that investment remains underdeveloped. Among the same 839-respondent base, only 45.1% of organizations have audit logging for AI agent actions [3], and just 58.6% mandate automated test coverage thresholds for AI-generated code [3]. These gaps are not minor oversights, they represent material risk exposure as AI-generated code moves into production environments. For consulting firms, this combination of rising investment intent and incomplete risk controls is a textbook advisory opportunity. Enterprises need help building the governance frameworks that make AI-assisted development safe to scale.

Operational AI Is Gaining Ground, Raising the Stakes

AI integration in software operations is also deepening. Some 57% of organizations have deployed AI for automated root cause analysis in observability workflows [3], signaling that AI is moving beyond the development phase and into production operations. This expansion raises the governance stakes further: as AI agents take on more autonomous roles across the software lifecycle, the absence of audit logging [3] and consistent verification practices [3] becomes a systemic risk rather than a departmental one. FTI's record revenue quarter [1] suggests enterprises are already seeking outside expertise to manage this complexity. The firms that establish credibility in AI governance advisory now will be well-positioned as agentic workflows become standard practice across the enterprise.

What to Watch

  • FTI segment revenue mix: whether technology advisory engagements grow as a share of total revenues starting in Q4 2026 [1]
  • AI governance adoption rate: how quickly organizations close the audit logging gap from the current 45.1% baseline among 839 surveyed as agentic deployments scale [3]
  • SLE budget conversion: whether the 45.6% of decision-makers planning investment increases translate to closed deals in Q4 2026 [3]
  • Agentic workflow maturity: how fast enterprises move beyond individual developer assistance tools toward integrated, multi-agent development platforms [3]

Sources

1. FTI Consulting Reports Second Quarter 2026 Financial …, Fticonsulting, July 2026

2. 2H 2026 Software Lifecycle Engineering Market Sizing & Five-Year Forecast, Futurum Research, July 2026

3. 2H 2026 Software Lifecycle Engineering Global Enterprise Decision Maker Survey Report, Futurum Research, July 2026

4. 1H 2026 Software Lifecycle Engineering Decision Maker Survey Report, Futurum Research, January 2026


Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.

Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.

Read the full Futurum Group Disclosure.


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Author Information

FuturumAI

This content is written by a commercial general-purpose language model (LLM) along with the Futurum Intelligence Platform, and has not been curated or reviewed by editors. Due to the inherent limitations in using AI tools, please consider the probability of error. The accuracy, completeness, or timeliness of this content cannot be guaranteed. It is generated on the date indicated at the top of the page, based on the content available, and it may be automatically updated as new content becomes available. The content does not consider any other information or perform any independent analysis.

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