by John Fuggles

The finance AI readiness assessment

An easy-to-use assessment designed to benchmark your finance function’s AI readiness and highlight the actions required to reduce risk, unlock efficiencies and accelerate transformation.

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Are you ready for AI? Something perhaps finance leaders are asking, or have been asked by their CEO, by their stakeholders and of course by consultants. But even within one organisation and withing the finance team alone that question has different meanings and likely, will get a different response.

Within the company, those responsible for the overall efficient operation of the business may well consider how the current finance strategy aligns with the wider company ambitions for AI. How better to optimise all processes, which technologies to use across the business, and taking an altogether broader view of the question, and the needs of the business.

Others may take a focus more on the skills and people element. What training is needed, both from a practical application point of view but also from the perspective of governance and risk, security and policies more generally. When and how to use AI as much as what will be the benefits of. What about bias, and business ethics?

For the finance function itself these considerations all apply. What systems would benefit the finance function is usually a sum of two parts. What can be done to remove the mundane, do the ‘heavy lifting’ and automate. How to spot outliers and manage these versus those that sit within the parameters permitted. Allowing the finance team to bring value-add insight to the function and to the business.

Very often AI readiness is measured through the lens of “what could we do” more than “are we ready”. Being more focused on the latter at the start will deliver greater benefits later. And to do that we need a process and a mechanism for scoring.

Our recommendation is a simple five-point scoring system (1 = not started, 5 = already there) mapped against short, medium and long-term objectives. Overlayed with a measure of risk and mitigations. This total view will highlight what can be done now, what needs to be addressed first and where the gains can be made now, with a view still on the long-term objective.

The tables below are intentionally easy to use and complete and will give you a good idea of your AI readiness. No two people in the same team or department will complete them the same so it’s wise to have multiple people filling this out and then use the different scores to form a debate on what the collective answer should be.

Why this matters

Investing in AI is not a matter of plugging in a widget to existing processes or technologies, or extended the usability of existing technology with additional functionality. AI brings with it a significant number of advantages, as well as challenges. It does not sit isolated from matters related to GRC or to the impact on personnel.

To make the right decisions and to get a better rate of return on any AI investment, whether financially, or operationally, it matters to understand the the current status and identify what else should be addressed.

The scoring mechanism we have developed at VantagePoint will help you in identifying pain points and how a programme of AI enablement can solve challenges you have today whilst motivating the team to want to do more than they are today.

This will help you:

Reduce risk

Boost overall performance

Increase data confidence

Align with other transformation programmes and initiatives

Complete the free survey and get the results

Strategic alignment	Evaluation question	Scoring criteria (1–5)
Finance AI vision	Does the finance function have a clear AI vision aligned to business strategy?	1 - No AI vision. 3 - Informal discussions. 5 - Clearly documented AI vision and roadmap
Executive sponsorship	Is there C-level commitment and sponsorship for AI initiatives in finance?	1 - No sponsorship. 3 - Some support. 5 - Executive championing AI use in finance
Use case prioritisation	Have finance-relevant AI use cases been identified and prioritised?	1- No use cases identified. 3 - Brainstormed but not ranked. 5 - Prioritised list aligned to business impact
Cross-functional collaboration	Is the finance function collaborating with other teams e.g. IT?	1 - Siloed. 3 - Occasional interaction. 5 - Regular integrated planning sessions

Data readiness	Evaluation question	Scoring criteria (1–5)
Data availability	Are financial data sources accessible and consolidated?	1 - Disparate. 3 - Partially integrated. 5 - Centralised, able to be interrogated
Data quality and accuracy	How reliable and accurate is your finance data?	1 - Frequent errors. 3 - Occasional data issues. 5 - High-quality, verified data
Master data management	Are chart of accounts, cost centres etc. standardised across systems?	1 - Inconsistent. 3 - Mostly aligned. 5 - Fully standardised
Data governance and security	Are there data controls and compliance policies for financial data?	1 - No formal governance. 3 - Informal guidelines. 5 - Documented and enforced policies

Process and automation	Evaluation question	Scoring criteria (1–5)
Process standardisation	Are core finance processes standardised?	1 - Highly variable. 3 - Some standardisation. 5 - Fully standardised
Use of RPA/automation	Is robotic process automation (RPA) or rule-based automation in use?	1 - No automation. 3 - Limited use. 5 - Multiple automation initiatives
AI opportunity mapping	Have you mapped which processes are AI-suitable (e.g. forecasting, reconciliation)?	1 - No mapping. 3 - High-level list. 5 - Detailed AI opportunity assessment completed
System integration readiness	Can AI solutions be integrated into existing finance systems?	1 - No / Don’t know. 3 - Some integration options. 5 - Fully integrated

People and skills	Evaluation question	Scoring criteria (1–5)
AI awareness	Do team members understand AI concepts and their relevance?	1 - No understanding. 3 - Some awareness. 5 - Team-wide training programmes in place
Data literacy	Are you comfortable working with data and analytics tools?	1 - Low data literacy. 3 - Basic statistics knowledge. 5 - Skilled in predictive models
Change management capacity	Is there a culture of innovation and openness to AI change?	1 - Resistant to change. 3 - Slow adoption. 5 - Keen for experimentation and innovation
Upskilling programmes	Are there learning programmes to build AI skills?	1 - No programmes. 3 - Ad hoc learning. 5 - Regularly training with measures

GRC	Evaluation question	Scoring criteria (1–5)
AI risk assessment	Have you assessed risks related to using AI? e.g. bias, errors, hallucinations	1 - No risk assessment done. 3 - Informal discussion. 5 - Risk framework exists and in use
Regulatory compliance	Are AI systems aligned with regulations?	1 - No awareness. 3 - Some controls exist. 5 - Clear AI compliance framework
Model auditability	Are AI model decisions explainable and auditable?	1 - No visibility into AI models. 3 - Partially. 5 - Fully auditable models
Ethics and accountability	Are ethics, fairness, and accountability embedded in AI programmes?	1 - No ethics framework. 3 - Discussed but not enforced. 5 - Documented principles and accountability

What does this all mean?

Use the scoring criteria below, benchmark your AI readiness and identify your next steps. Not only will this help identify the right approach to take but will, we hope, give you areas to consider that could be developed internally, as well as talking to us at VantagePoint.

<50: you are a long way from ready.

The continual development of AI presents an opportunity to finance teams to reduce the amount of manual, repetitive tasks and focus on initiatives that help move the organisation forward. AI can reduce inefficient processes, automate workflows and remove delays, analyse and present data in a digestible format and utilise the knowledge gleaned to improve processes and communication next time. But very often, just knowing where to start is the biggest hurdle.

VantagePoint AI labs is a one-day session designed to future-proof your finance function through a mixture of presentations and collaborative exercises, which diagnose the present state of your finance function from a technological perspective. You’ll leave the session with actionable steps to further prepare and integrate developing AI technology into your finance strategy. 

AI Labs will provide you with a roadmap to leverage AI in your finance function and benefit from the reduction in administrative workload. 

Find out more about AI labs

51-70: you clearly have some good first steps but there is more you can do.

Discovery is the first step in our approach to better understand where you are today and what the future potential could be. Investing in AI is only part of finance transformation. It matters therefore to take a holistic approach first but with a focus on what AI can do for you.

Our discovery process is a proven first step in understanding your needs and identifying what good looks like for the future. Defining needs and aligning them with what is possible and what could practically be delivered will create a plan to accelerate your AI plans.

The discovery is the first step, leading quickly to a presentation from us and a discussion with you on what should be done next. This is a free service designed to help you and align us both to move forward together.

71-85: a great position to be in. Some shaping required to prepare you.

Despite great progress at VantagePoint, we believe this presents an inflection point where innovation must evolve into a scalable and structured transformation programme, to ensure AI is embedded as a core capability across the finance function.

Success at this stage comes with a cost. Evaluating return on investment, user experience and alignment with business objectives is critical for long term success and to maximise on existing investment. We will work with you to develop a roadmap and identify the most impactful and repeatable use cases. From there our vendor selection, process and AI expertise will plug the gaps to maximise the opportunity.

86+: you are well placed and should be investing in tools and systems to accelerate the use of AI in your finance function