FTI Consulting

fticonsulting.com

FTI should be evaluated as a multidisciplinary consultancy with specific technology delivery practices, rather than as a technology-only provider. Its commercial offerings span technology strategy, software and AI development, cybersecurity response, information-governance implementation and managed legal technology services. Buyers can procure assessments, prototypes, implementation work or ongoing services, but these delivery models are not interchangeable. Its case studies establish hands-on AI development while also showing engagements limited to governance, vendor selection or integration recommendations. Procurement should identify the responsible practice and distinguish FTI-owned delivery from client or external-vendor responsibilities. ^[1] ^[2] ^[3] ^[4] ^[5] ^[6] ^[7]

Services and delivery

AI strategy advisory

Advisory. Assesses AI capabilities, prioritizes initiatives and develops business cases and technology roadmaps to guide investment and implementation planning. ^[2]

AI and machine-learning development

Implementation. Develops tailored automation, forecasting, optimization and generative-AI solutions, with scope ranging from proofs of concept to production solutions. Individual engagements require confirmation of deployment and support responsibilities. ^[2]

Responsible-AI advisory

Advisory. Assesses AI risks, regulatory considerations and models or solutions to help buyers establish appropriate governance and evaluation controls. ^[2]

Data strategy and architecture advisory

Advisory. Advises on data strategy, architecture, management and readiness for AI initiatives. This is a distinct data-foundation offering rather than evidence, by itself, of model development. ^[2]

IT rationalization execution

Implementation. Designs and executes technology rationalization programs within its digital transformation practice. Scope should be specified separately from outsourcing strategy and technology-vendor advisory. ^[3]

Digital product development

Implementation. Develops digital products and applications within technology-led transformation programs. The offering references IoT, cloud computing, cybersecurity, machine learning and AI, without establishing a standard platform stack. ^[3]

E-discovery technology implementation and support

Implementation. Provides e-discovery software deployment, support, workflow design and project management. The service page names Relativity, Reveal and Nuix Discover. ^[6]

Managed e-discovery

Managed services. Provides software hosting, staffing, project management and outsourced e-discovery operations for legal matters. Technical managed services should be scoped separately from document-review staffing. ^[6]

Cybersecurity readiness and strategy advisory

Advisory. Provides tailored readiness assessments and exercises, cybersecurity strategy and risk-program development. This technical advisory scope is distinct from cyber-related reputation and stakeholder communications. ^[4]

Cyber incident response and recovery

Implementation. Provides technical incident response and recovery services. Buyers should establish the contracted response scope, escalation process and recovery responsibilities. ^[4]

Information-governance implementation

Implementation. Implements information governance, data mapping and disposition, with Microsoft 365 compliance-program design also documented. The offering addresses information control and privacy rather than establishing AI development capability. ^[5]

Managed privacy programs

Managed services. Designs, builds and operates data privacy risk-management capabilities through privacy-program managed services. Buyers should distinguish operational responsibilities from advisory deliverables. ^[5]

Company details

Technology and platforms

Platform evidence is engagement-specific. FTI names Relativity, Reveal and Nuix Discover for e-discovery services and Microsoft 365 for compliance-program design. Its banking KYC case identifies Python, Pandas and Apache Spark for data transformation; that does not establish a firm-wide AI stack. ^[6] ^[5] ^[8]

FTI describes IQ.AI as combining proprietary workflows, expertise and generative AI for investigations, antitrust review, litigation and breach analysis. Its release also describes specialist data scientists applying generative AI to a law firm’s document population. This supports service-enabled delivery, but does not establish standalone licensing terms. ^[9]

Track record

For a multinational bank, FTI reports developing and piloting an AI-enabled KYC refresh platform. Deliverables included a policy decision tree, integrated workflows, custom AI models and an agent automating tests and actions. The case establishes development and pilot work, not a documented long-term production support arrangement. ^[8]

For an American educational publisher, FTI reports building a machine-learning predictive engine with SKU- and region-level forecasts. It reports freeing working capital equivalent to 10% of annual purchasing spend. This is a client-specific outcome; the described integration deliverable was recommendations rather than clearly documented production integration. ^[10]

A financial institution engaged FTI Technology for a Microsoft Copilot governance assessment involving technical testing, application-specific data-access evaluation, risk reporting and a future testing workflow. The case reports implementing a governance framework, not ownership of the institution’s entire Copilot rollout. ^[11]

For an advertising-solutions provider, FTI reports creating document-extraction pipelines and specialized AI chatbots. The functioning proof of concept was developed in six weeks and tested with more than 2,000 synthetic documents. The evidence supports prototype delivery rather than a completed production rollout. ^[12]

Scope and limitations

The supplied case studies largely anonymize clients. They establish FTI-reported engagement scope and outcomes, not independently checkable customer references.
Production integration, hosting, ongoing monitoring and support are not established for every AI engagement. Prototype and pilot evidence should not be treated as proof of full operational ownership.
The supplied evidence does not establish particular ERP implementation capabilities, named-cloud migration services or a standard firm-wide AI stack.
Proprietary-tool licensing, model providers, data residency and intellectual-property terms require verification for the proposed engagement.

Questions to ask

Which FTI practice will own delivery, and which responsibilities remain with our team or external vendors?
Does the statement of work cover assessment, prototype, production deployment, ongoing operation, or only some of these stages?
Can you provide comparable production references, acceptance criteria and model-validation results?
Which platforms and model providers are proposed, and what constraints apply to data residency, security and integration?
Who owns custom code, models and workflows, and what separate proprietary-tool licensing is required?
What post-launch monitoring, support, incident escalation and service levels are included?

Overview