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Common Questions

Frequently Asked Questions

Everything you want to know about working with Software Equality - answered directly and honestly.

About Our Services
ADLC (AI Development Lifecycle) is our proprietary framework for building AI systems. It covers 7 phases: Discovery, Specification (using SPARC), Design, Development, Evaluation, Deployment, and Governance. Each phase has defined inputs, outputs, and governance checkpoints. It ensures every project is fully documented, testable, and auditable - critical for enterprise AI that needs to satisfy legal and regulatory scrutiny.
We primarily work with enterprise organisations (250+ employees) and growth-stage technology companies that are serious about deploying AI at scale. We've worked with organisations ranging from 50-person scale-ups to global enterprises with tens of thousands of employees. What matters more than size is whether you're genuinely committed to deploying AI properly - not just experimenting.
It depends on scope. A focused Agentic AI project with a well-defined use case typically takes 60-90 days from SPARC specification to production deployment. A full AI governance framework usually takes 3-6 months depending on the number of AI systems in scope. AI consultancy and strategy engagements typically run 4-12 weeks. Bootcamp training can be delivered in 2-4 days.
We strongly prefer fixed-price engagements with clearly defined deliverables. Our SPARC methodology is specifically designed to create the clarity needed for accurate fixed-price scoping. This aligns our incentives with yours - we don't benefit from projects running over time. For ongoing advisory relationships, we use monthly retainer arrangements with defined deliverables.
Three things: (1) We actually build what we specify - no handoff to a different "delivery team". (2) We're honest about what AI can and cannot do. We won't oversell a use case to win work. (3) We transfer knowledge to your team throughout the engagement, so you're not dependent on us long-term. Larger consultancies often benefit from creating dependency. We don't.
Yes. All production systems we deploy come with a 30-day hypercare period included. After that, we offer optional maintenance and monitoring retainers. For organisations that want continuous AI capability support, we also offer fractional AI leadership services (part-time CTO/AI Director arrangements).
Both. Our Foundations and Professional tier bootcamps are available in both formats - online via video conference with interactive labs, or in-person in London or at your offices. Enterprise tier programmes are typically delivered on-site to maximise team cohesion and hands-on work on your actual use cases. Contact us to discuss which format works best for your team.
Data privacy and security are built into every engagement from day one. We apply privacy-by-design principles, minimise data access to what's strictly necessary, operate under NDAs and DPAs as standard, and can work within your security perimeter if required (on-premise delivery, VPN access, etc.). For sensitive sectors like healthcare and financial services, we have extensive experience navigating sector-specific data requirements.
It's a genuine 45-minute conversation - not a sales pitch. We'll ask about your organisation, your AI ambitions, and your current challenges. We'll share our honest perspective on what's achievable and how we'd approach it. If there's a good fit, we'll outline what a proposal would look like. If there isn't, we'll say so clearly and might even point you toward a better resource. No obligation, no hard sell.

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The Numbers Behind Common AI Questions
Data to contextualise the most frequent questions about enterprise AI adoption
85%
Of AI projects fail primarily due to unclear objectives & poor data
Gartner, 2024
6
Weeks average from kickoff to first working AI sprint under ADLC
Software Equality, 2025
39%
Only of organisations are measuring actual business impact from AI spend
McKinsey State of AI, Nov 2025
72%
Of UK SMEs lack in-house AI expertise — external expertise bridges the gap
Tech Nation / DSIT, 2024
£2,495
Starting price for AI Bootcamp — often the fastest path to ROI clarity
Software Equality, 2025
51%
Of AI-using organisations have experienced at least one negative AI outcome
McKinsey, Nov 2025
Top Reasons AI Projects Underperform (Gartner 2025)
Unclear objectives
72%
Poor data quality
68%
No governance
55%
Skill gaps
51%
Tool-first thinking
47%
No exec buy-in
39%
“AI does not fail because the technology is bad. It fails because the business problem was never properly defined, or the data was not ready to support the ambition.”
Gartner Data & AI Summit, 2025
ADLC Framework: How We Fix Each Problem
1
Discovery & Scoping
Crystal-clear objectives and measurable success criteria before any build
2
Data Readiness
Data audit and pipeline design in sprint week 1
3
Governance by Design
EU AI Act & ISO 42001 baked in from day one
4
Capability Transfer
Every sprint builds your team alongside the product
Sources: Gartner Data & AI Summit 2025 • McKinsey State of AI (Nov 2025) • Tech Nation / DSIT UK AI Review 2024 • Software Equality delivery data 2025

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Research Intelligence

AI Adoption: The Data Behind Common Questions

Enterprise leaders ask the same questions about AI. Here is what the leading research actually shows.

Common AI Questions — What the Research Says
QuestionResearch AnswerSource
"How many companies are using AI?"88% use AI in at least one function; only 1% have reached full maturityMcKinsey 2025
"What ROI can I expect from AI?"26% productivity gain (software dev), 14-15% (customer support), 73% output (marketing)Stanford 2026
"How long does AI deployment take?"8–16 weeks for production agentic systems; 90-day full deployments achievableSE Data
"What is an AI agent?"Autonomous system that plans and executes multi-step workflows without human interventionMcKinsey 2025
"Do I need AI governance?"EU AI Act full application August 2026; 51% of orgs have already seen negative AI consequencesEC AI Act 2026
"How big is the AI skills gap?"63% cite skills gap as #1 barrier; 59/100 workers need reskilling by 2030WEF 2025
"Will AI replace jobs?"170M new jobs created, 92M displaced = 78M net new jobs by 2030WEF 2025
"What separates AI leaders from laggards?"Workflow redesign, senior leadership commitment, agent scaling in 3+ functionsMcKinsey 2025
Sources: McKinsey State of AI November 2025 • Stanford HAI AI Index 2026 • WEF Future of Jobs 2025 • EU AI Act (Regulation EU 2024/1689)
88%
using AI — but only 33% are scaling beyond pilots
McKinsey Nov 2025
170M
new jobs projected by 2030 from AI transformation
WEF Jan 2025
Aug 2026
EU AI Act full application deadline
EC AI Act
26%
software dev productivity gain from AI coding tools
Stanford 2026
AI Skills Gap — % Citing Barrier
63% % Citing Barrier
63% of organisations cite skills gaps as their primary barrier to AI adoption. Of those, 85% are investing in upskilling programmes — but 71% say internally-led training fails without external expert guidance.

Source: WEF Future of Jobs Report 2025