AI advisory services
AI with a purpose.
Trust by design.
Start with what your business needs to achieve.
dForce’s AI advisory services help you identify worthwhile opportunities, assess readiness and put practical governance in place. We connect AI decisions to your operating model, technology and the outcomes that justify the investment.
A clear purpose. Defined boundaries. Accountable ownership.
The business case comes first
An AI capability is a starting point.
The outcome gives it purpose.
An accessible tool or a compelling demonstration can make the next step seem obvious. Your business deserves a considered decision: what needs to improve, what that improvement is worth and whether AI is the right way to achieve it.
That might mean reducing administrative effort, improving access to reliable information or helping people identify exceptions sooner. We help define a baseline, agree measures and assess the costs, risks and changes involved.
Our advisory services bring the Operating Model Canvas and Operating Model Diagnostic together to examine the processes, responsibilities and operating rules behind the opportunity.
Before you begin
Make the decision clear.
Our focus
Practical foundations for responsible AI.
Turn broad principles into decisions your teams can apply, from selecting a use case to operating it day to day.
Strategy & readiness
Prioritise use cases against business value, feasibility and risk. Assess the processes, data, skills and systems needed to support them.
Policy & ownership
Define acceptable use, decision rights, approval routes and accountable owners. Make policies understandable for the people expected to use them.
Data & privacy
Examine data quality, access, retention and supplier handling. Identify the privacy questions and specialist reviews required for the proposed use.
Fairness & transparency
Consider who could be affected, test for uneven outcomes and explain where AI is used. Establish routes for people to question or challenge its outputs.
Architecture & integration
Understand how AI fits into your applications and data flows. Define permissions, interfaces and controls before introducing new capabilities.
People & assurance
Prepare teams to use AI appropriately, recognise its limitations and escalate concerns. Agree monitoring, review and change responsibilities.
Explore our application architecture and solution design services for the wider technology foundations.
Agentic AI & human oversight
When AI can act,
the boundaries matter.
An assistant that drafts an answer and an agent authorised to update a record require different controls. The scope of access and action should be explicit, proportionate to the task and understood by the people responsible.
We help you define those boundaries before deployment, including what requires human approval and how your team intervenes when something goes wrong.
Permission to act
Specify permitted systems, data and actions. Limit access to what the task requires.
Approval & escalation
Set review points for consequential actions, exceptions and uncertain results.
Traceability & recovery
Record actions and decisions, define how to pause activity and plan how changes can be corrected.
Ongoing review
Reassess behaviour after changes to models, prompts, data, integrations or supplier capabilities.
From opportunity to operation
Start with a defined use case.
Earn the decision to scale.
01
Define the outcome
Agree the business problem, baseline, benefit owner and measures of success. Decide whether AI is appropriate for the task.
02
Design the controls
Review data, process and technical readiness. Set operating rules, responsibilities, approval points and acceptance criteria.
03
Pilot & evaluate
Test within a bounded scope. Compare results with the baseline, examine failure cases and gather feedback from the people using it.
04
Enable & assure
Proceed when the evidence supports it. Prepare teams, assign operational ownership and review performance, risks and benefits over time.
Where a use case is ready for delivery, our implementation and integration services help connect the agreed design to your operational systems.
What you can expect
A clear basis for the next decision.
Depending on the agreed scope, an engagement can provide:
An outcome brief
The problem, baseline, intended benefits, ownership and success measures.
A readiness assessment
Prioritised use cases, dependencies, risks and gaps to address.
Practical governance
Operating rules, approval routes, responsibilities and review arrangements.
A delivery & assurance plan
A bounded pilot, acceptance criteria, enablement needs and measures for ongoing review.
Guidance & reference points
Ground the conversation in established guidance.
The NIST AI Risk Management Framework provides a voluntary framework for managing AI risks. The ICO’s guidance on AI and data protection addresses the use of personal data in AI systems.
These are useful reference points when shaping governance for your use case, alongside the requirements applicable to your organisation.
From Insight to Impact.
What should AI help your business achieve?
Whether you are exploring an opportunity, reviewing existing use or preparing for agentic AI, start with the outcome. We’ll help you assess the next step and the foundations needed to take it with confidence.