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Transformation

From AI uncertainty to real-world outcomes

Talent, training and transformation to take your organization from AI ambition to AI advantage. A structured journey from readiness to results, built on the belief that technology alone doesn’t create impact. People do.

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#1

in technology talent

8

specialist brands

3

services: talent, training, transformation

The window to act is now

Industry analysts predict that by 2029, the highest-performing enterprises will have reengineered around 80% of their back-office process flows and 50% of their front-office flows by leveraging AI. The organizations that build real capability now, not just buy tools, will be the ones that pull ahead.

The AI quandary

Boards want game-changing AI, but most organizations start with everyday AI. Closing the gap between the two isn’t a technology problem, it’s a question of foundations: data, talent, governance and a culture of experimentation.

Everyday AI
Most organizations start with copilots, assistants and automation. These tools can create real productivity gains, but around 74% of current value comes from time saved rather than measurable financial return. Everyday AI is an important foundation, but it is not the end goal.
Game-changing AI
This is where AI starts to drive revenue, create new products and build competitive advantage. It is also where Boards want to be. Getting there requires clean data, specialist talent, strong governance and a culture that can test, learn and scale. Many organizations are not ready yet, although interest in agentic AI is accelerating.

The agentic spectrum. Where the value is heading

Copilot assistants
Basic agents
Multi-agent systems
Autonomous agents

The data the Board needs to see

Recent independent research shows where enterprise AI is delivering value, where it is falling short and why success depends on a structured approach to strategy, talent, governance and execution.

95%

of enterprise GenAI pilots delivered no measurable P&L impact (MIT NANDA, 2025)

~67%

success rate with specialist vendor partnerships vs ~33% for internal builds (MIT, 2025)

39%

of workers’ core skills will change by 2030 (WEF Future of Jobs, 2025)

85%

of employers now offering upskilling in response (WEF, 2025)
Sources: MIT NANDA, The GenAI Divide: State of AI in Business 2025; World Economic Forum, Future of Jobs Report 2025.

Why most AI investments fail and what separates the 5%

Despite $30–40 billion of enterprise GenAI investment, around 95% of pilots have delivered no measurable financial impact, according to MIT NANDA’s The GenAI Divide: State of AI in Business 2025. The issue is rarely model quality alone. More often, the gap comes from poor integration, unclear use cases and a lack of internal capability to adopt the technology properly. The 5% that succeed take a different approach, combining the right strategy, skills and execution to turn AI investment into measurable business value.

What separates the 5%

Drawn from MIT NANDA’s analysis of 300+ public AI deployments and 150+ executive interviews, and exactly where our Assess, Design, Deliver method focuses.

Integrate, don’t bolt on

Solutions that adapt to your workflows and data, not generic assistants stapled to the side. Integration over hype.

Partner with specialists
Vendor-led approaches succeed around 67% of the time; internal-only builds succeed at roughly one-third that rate.
Start where ROI lives
Most budget goes to sales and marketing pilots; MIT found the biggest measurable ROI in back-office automation. Follow the value.
Build learning systems

Beat generic, static sytems with tools that learn from your context, processes and people, and improve with use.

Govern responsibly

Clean data, security, compliance and responsible-AI policies that are built in from day one, not bolted on after the first incident.

Grow capability continuously

Role-based training, “ask an expert” coaching and an AI-fluent workforce, instead of a one-off course.

AI is a people challenge, not just a technology challenge

AI won’t replace your workforce, but it will change how people work across every role. The people who know how to use AI effectively will move faster, make better decisions and create more value.

Building that capability takes more than a one-off training session. Businesses need continuous learning that keeps pace with change, tailored content that reflects each role and team, and access to expert support when practical questions arise. They also need clear education and governance, so both business and IT teams can use AI safely, confidently and at scale.

Our approach: Assess, Design, Deliver

A structured journey from AI readiness to real-world outcomes. Fast, iterative and grounded in evidence.

01 Assess
Readiness & strategy

AI Readiness Assessment across Strategy, Data, People and Governance (including responsible AI); use-case evaluation by function with business-process review; a Fit-for-AI plan and prioritized roadmap.

02 Design
Capability & governance

Tailored training programs for exec, technical and business teams; Centre of Excellence and AI Fusion Team structures; governance frameworks including responsible AI.

03 Deliver
Talent & solutions
Specialist talent placed into your teams; AI solutions built and deployed; ongoing support, coaching and “ask an expert” access.

What you get at each stage

The deliverables that turn Assess, Design, Deliver from a tagline into a contract.
From Assess

AI Readiness Assessment across Strategy, Data, People and Governance; Use-case evaluation by function; Fit-for-AI Plan; Use-Case Roadmap; Prioritized Action Plan.

From Design

Role-based training programs for exec, technical and business teams; Center of Excellence and AI Fusion Team designs; Responsible-AI governance framework target operating model.

From Deliver

Specialist talent placed into your teams; AI solutions built and deployed in production; Ongoing coaching, “ask an expert” support and continuous capability uplift.

It starts with an AI Readiness Assessment

A comprehensive evaluation across four dimensions to create your Fit-for-AI plan.
Strategy & Leadership
Current vs future state, Board vision, investment appetite, competitive positioning and strategic AI priorities.
Data & Technology
Infrastructure maturity, data quality and accessibility, cloud readiness and the integration landscape.
People & Culture

AI literacy across the organization, role readiness, change appetite, training gaps and talent pipeline.

Governance & Risk
Security posture, compliance frameworks, responsible-AI policies and risk-management readiness.

Enterprise AI training that builds real capability

Role-specific programs that build capability, not just awareness. Role-based pathways for developers, consultants, business users and executives; instructor-led sessions with hands-on labs and live projects; continuous coaching with “ask an expert” support; our Hire, Train, Deploy model for net-new AI talent; and reskilling for existing teams to embed AI into daily workflows.

Where AI is delivering value today

Here are nine areas where organizations are seeing measurable returns from AI, with the strongest opportunities in back-office functions, where MIT research points to the highest ROI, as well as front-office and knowledge-work areas where productivity gains can scale quickly.

Finance & accounting

AP / invoice automation · Financial close acceleration · Anomaly detection

Supply chain & operations

Demand forecasting · Supplier risk · Inventory optimization

HR & people

Talent screening · Onboarding copilots · Employee Q&A

Legal & contracts

Contract review · Clause extraction · Redlining

IT operations

Ticket triage · Knowledge search · Incident summarization

Risk & compliance

Regulatory monitoring · audit prep · control testing

Customer service

Agent assist · Intent routing · Call summarization

Sales & marketing

Account research · Opportunity prioritization · Content generation

Software engineering

AI-assisted coding · Test generation · Code review

Our proven results

Delivering AI capability for leading global organizations.

Big 3 Global Consulting Firm · Agentforce Certification

A bespoke intensive Salesforce Agentforce program, designed and delivered in person across EMEA and the US for mixed-ability consultants with a 78% certification pass rate.

Mid-Size Global Technology Consulting Firm · AI Document Intelligence
Built and deployed a production-ready AI platform for contract digitization and intelligence, turning manual workflows into automated, scalable processes. Production MVP in months on a scalable AWS architecture.
World Top 15 Global Bank · Data Engineering + AI/ML

A training-and-deployment program covering Java, Spring Boot, Git, Kubernetes, Flink and Apache Kafka, plus AI & ML, prompt engineering, ethics, governance and LLMs.

Big 4 Audit & Consulting Firm · Gen AI + ServiceNow / Pega

Building the ability to work with Gen AI LLMs across the ecosystem, with governance, risk and ethics. 100 consultants trained and deployed over 12 months.

What leaders want to know

Research from MIT found that while many AI pilots fail to deliver measurable business value, the most successful organizations take a different approach. They focus on clear business use cases, integrate AI into existing workflows, invest in the right skills, establish strong governance and build capability over time. Our Assess, Design, Deliver methodology is built around those principles, helping organizations move beyond experimentation and focus on outcomes that can be measured and scaled.

The Assess phase can produce a Fit-for-AI Plan and prioritized roadmap within weeks, not months. From there, Design and Deliver run in iterative cycles, helping you see practical progress in the first quarter, from trained teams and deployed solutions to working governance. Broader value then builds as adoption scales.

Governance is built into our approach from the start. It is one of the four dimensions of our AI Readiness Assessment and a core part of the Design phase, where we define a responsible AI framework covering security, compliance, data quality, model risk and human oversight. This helps organizations move faster with clear guardrails in place, so AI can be adopted safely, responsibly and at scale.

Hyperscalers provide the platforms. Large consultancies often focus on strategy. We focus on the capability needed to turn AI plans into working business outcomes. That means bringing together specialist talent, role-based training and practical delivery support, so organizations can build, adopt and scale AI with the right people in place. Through our specialist brands, we give businesses access to AI, cloud, data and platform professionals at a depth and scale that generalist providers cannot easily match.

We agree success measures during the Assess phase, before delivery begins. These typically include capability measures such as people trained, certified or deployed, delivery measures such as solutions in production, automation rates and reduced cycle times, and business measures such as cost saved, revenue enabled or risk reduced. The Fit-for-AI Plan defines what success looks like from the start, so every stage is measured against clear outcomes.

Let's start your AI journey

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Role-based training, specialist talent and hands-on delivery to embed AI across your organization.

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