Industries
Solutions shaped by sector, workflow and responsibility
The underlying technology is often similar across sectors. What differs is the workflow, the information involved, the professional accountability and the level of oversight the work requires.
Eight sectors
Sector considerations we work through
Each sector below sets out typical transformation challenges, the consultancy areas that usually apply, the solution capabilities that may be appropriate, the training likely to be needed and the governance considerations that shape the design.
01Corporate and professional services
- Typical transformation challenges
- Information spread across systems, repetitive document preparation, inconsistent reporting, and pressure to adopt AI without a clear position.
- Suitable consultancy areas
- Opportunity assessment, use-case prioritisation, generative AI strategy, vendor evaluation, implementation roadmap.
- Possible solution capabilities
- Knowledge assistants over approved material, document intelligence, drafting support with review, workflow automation, reporting dashboards.
- Training requirements
- Executive briefings for partners and directors, workforce training on verification and confidentiality, technical development for internal IT.
- Governance and risk considerations
- Client confidentiality, professional accountability for advice, records and retention, and clarity on what may be processed by which tool.
02Small and medium-sized businesses
- Typical transformation challenges
- Limited technical capacity, manual administration, fragmented data, and uncertainty about which tools justify their cost.
- Suitable consultancy areas
- AI-readiness review, use-case discovery, feasibility assessment, platform evaluation, staged roadmap.
- Possible solution capabilities
- Focused automation of one high-volume process, a small knowledge assistant, a practical dashboard, integration between existing tools.
- Training requirements
- Short practical workforce sessions and a briefing for the owner or leadership team.
- Governance and risk considerations
- Proportionate controls, personal-data handling, dependency on a single supplier, and realistic ownership after handover.
03Technology and engineering
- Typical transformation challenges
- Prototypes that do not reach production, unclear evaluation practice, integration debt, and rising expectations around agentic features.
- Suitable consultancy areas
- Architecture guidance, feasibility assessment, evaluation and monitoring design, responsible AI planning.
- Possible solution capabilities
- Retrieval and agentic components, evaluation harnesses, observability layers, API integration, internal developer tooling.
- Training requirements
- Technical team development, agentic AI masterclasses, evaluation and observability workshops.
- Governance and risk considerations
- Excessive agency, prompt injection through untrusted content, secret handling, model and dependency change control.
04Universities and research organisations
- Typical transformation challenges
- Rapid uncharted use of AI tools in teaching and research, unclear integrity expectations, and research ideas that stall before prototype.
- Suitable consultancy areas
- Research and innovation advisory, responsible AI planning, technical project formulation, capability assessment.
- Possible solution capabilities
- Evidence and literature retrieval systems, document intelligence for research material, research data platforms, prototype development.
- Training requirements
- Responsible AI in research, AI-assisted research workflows, technical programmes for postgraduate and staff groups.
- Governance and risk considerations
- Research integrity, ethical approval, data-sharing agreements, attribution and verification of AI-assisted work.
- Boundaries
- We do not promise publications, funding or research results, and we do not imply institutional affiliation.
05Healthcare organisations
- Typical transformation challenges
- Administrative burden, fragmented documentation, and interest in AI where clinical risk and regulation must be respected.
- Suitable consultancy areas
- Readiness and data-readiness assessment, feasibility assessment, responsible AI planning, governance workshops.
- Possible solution capabilities
- Administrative and documentation support, policy and guideline retrieval for staff, operational dashboards, document intelligence for non-clinical records.
- Training requirements
- Executive briefings on risk and governance, workforce training on confidentiality and verification, technical sessions for informatics teams.
- Governance and risk considerations
- Patient confidentiality, lawful basis for processing, human accountability for every clinical decision, and clear limits on the system’s role.
- Boundaries
- Systems are designed to support qualified professionals. We do not claim diagnosis or treatment capability, clinical validation or hospital deployment, we do not promise patient outcomes, and high-stakes use requires professional oversight.
06Public-sector institutions
- Typical transformation challenges
- High enquiry volumes, extensive policy documentation, legacy systems, and accountability requirements that must be visible.
- Suitable consultancy areas
- Digital-maturity assessment, opportunity prioritisation, responsible AI planning, vendor evaluation, roadmap development.
- Possible solution capabilities
- Policy and procedure assistants for staff, document and evidence intelligence, service dashboards, controlled workflow automation.
- Training requirements
- Leadership briefings, workforce training on responsible use, technical development for internal digital teams.
- Governance and risk considerations
- Transparency, records management, equality and bias considerations, procurement constraints and auditability.
07Education and professional training
- Typical transformation challenges
- Learners using AI tools ahead of institutional guidance, administrative load, and material that is expensive to keep current.
- Suitable consultancy areas
- Responsible-use policy input, capability assessment, programme design advisory, platform evaluation.
- Possible solution capabilities
- Content preparation support with review, learner enquiry assistants over approved material, administration dashboards, assessment workflow tools.
- Training requirements
- Staff development on responsible use and verification, technical sessions for education technology teams.
- Governance and risk considerations
- Academic integrity, safeguarding, personal data of learners, and accuracy of information presented to students.
08Innovation teams and startups
- Typical transformation challenges
- Ambitious product ideas, limited evidence of feasibility, and pressure to demonstrate AI capability quickly.
- Suitable consultancy areas
- Feasibility assessment, architecture guidance, evaluation design, technical due diligence support.
- Possible solution capabilities
- Proof of concept, functional prototype, evaluation framework, integration with early customer systems.
- Training requirements
- Technical development for small engineering teams, agentic AI workshops, evaluation practice.
- Governance and risk considerations
- Honest capability claims to customers and investors, data handling in early pilots, cost control, and avoiding lock-in before requirements are stable.
No prior-project claims. The content above describes how we would approach work in each sector. It does not claim completed projects, deployments or client relationships in any industry.
Next step
Sector context changes the design.
Tell us the sector, the workflow and the accountability that applies. We will set out which capabilities are appropriate and which safeguards the design would need.