Blog: How much should public sector leaders invest in AI?

Every public sector leader I speak to wants to unlock the promise of artificial intelligence (AI). The ambition is clear: to deliver services faster, give staff back precious time, and improve experiences for citizens. The challenge is that budgets are tight, scrutiny is high, and no one wants to waste money on the wrong investment.

That tension often leads to the question… how much should we actually spend on AI?

The truth is that there is no single number. What matters isn’t the cost itself, but the outcomes achieved. Smart investment in AI means funding projects that deliver measurable change, not just experiments with technology.

At Infomentum, we help public sector organisations turn that ambition into practical, outcome-driven action. With deep experience in system integration, process automation, and AI solutions powered by Salesforce and MuleSoft, we help leaders build strategies that work with their existing technology and deliver a return they can prove.

Keep reading to learn how to take a strategic approach to AI investment, aligning spend with outcomes, integrating effectively, and creating impact you can demonstrate.

Aligning AI spend with strategic outcomes

AI investment should always start with outcomes. Leaders in the public sector are under constant pressure to balance efficiency with accountability, and every pound spent must be justified. Technology on its own rarely delivers that; it’s the connection between investment and impact that drives real results.

In policing, that might mean faster case resolution or better victim support. In healthcare, it’s freeing clinicians from admin so they can spend more time with patients. In higher education, it’s improving student engagement and retention through more personalised support.

Across the public sector, the goal is the same - more responsive, joined-up, and efficient services.

The question, then, isn’t “How much should we spend on AI?” but “What outcomes do we want to achieve, and what investment will help us get there?” When strategy leads the conversation, budget decisions follow naturally. It also helps leaders justify spend in human terms i.e. safer communities, healthier patients, better student experiences.

The most successful projects start with a crystal-clear understanding of the problem they’re solving. Whether that’s reducing call-handling times in policing, improving appointment scheduling in healthcare, or helping universities support more students with the same resources - the outcomes drive the investment, not the other way around.

What resonates most strongly with boards and funding bodies isn’t the technology itself but the ability to prove impact in human terms: safer streets, faster diagnoses, happier citizens. My advice? Start where the pain is greatest but where results can be demonstrated quickly. Early wins build confidence and unlock further funding. Once stakeholders see measurable improvement, they’re far more willing to expand investment.

Estimating spend without numbers

Once outcomes are clear, the next challenge is translating ambition into investment. Many leaders ask for a fixed figure, but AI rarely works that way. Costs and returns vary depending on scale, scope, and integration. A small pilot in one department looks very different from an enterprise-wide rollout, and both may be valid depending on goals.

Instead of chasing a single number, it helps to use a simple framework for decision-making. This keeps the focus on value rather than arbitrary cost lines and ensures leaders can weigh ambition against impact.

Our framework: approaching how much to invest in AI

1. Define the use case - Which workflows or services will AI enhance, and what outcomes are expected?
   
   
2. Assess technology requirements - What’s already in place, and will you need to extend with solutions like Agentforce AI?
   
   
3. Scale and scope - How many users, how much data, and how complex are the processes?
   
   
4. Plan for ongoing investment - Include updates, integration upkeep, and training to keep AI effective.
   
   
5. Benchmark scenarios - Compare a pilot, a medium-scale deployment, and a full rollout to map ambition against impact.

This framework often helps take the mystery out of AI investment. Leaders are relieved when we start mapping investment to impact. One healthcare leader told me recently, “We finally understood what we were buying - not just technology, but time back for our staff.” That’s when the conversation shifts from cost to value.

When I walk teams through this framework, we look at where they already have momentum - systems in place, existing data flows, or processes ripe for automation. By aligning ambition with practical readiness, decision-makers can approach budget discussions with confidence, not guesswork.

The role of integration in maximising ROI

No matter the ambition, integration is what turns AI from a promising idea into visible impact. Connecting AI to existing systems, particularly through Salesforce and MuleSoft, embeds it into service delivery rather than leaving it as a standalone tool.

Integrated solutions remove silos, cut duplication, and give leaders clear visibility of impact: hours saved, cases resolved faster, satisfaction scores rising. Every pound spent can be linked directly to tangible improvement.

Agentforce adds another layer of value by providing pre-built workflows and AI models that can be quickly integrated into your existing systems. It accelerates adoption, reduces the need for extensive custom development, and makes it easier to demonstrate early wins (more on this to come!).

Start small, scale fast with Agentforce Jumpstart

Many organisations tell us that the hardest part of adopting AI is simply knowing where to start. The potential is obvious, but choosing a safe, low effort first step can feel daunting. Our Agentforce Jumpstart removes that uncertainty by giving you a quick, guided way to experience real value without any setup on your side.

We kick off with a short consultancy session to understand your goals and the information you can share. From there, we build a small knowledge based agent in our own Salesforce environment using a sample of your content. Within days you can test it with real questions and see how AI can remove manual work, speed up responses and guide better decisions. The experience is free and shows where AI can have the strongest impact.

If that's not enough to convince you... one policing organisation used Jumpstart to test AI-driven case triage. Within weeks, an agent was categorising and prioritising incidents, reducing manual admin by nearly forty percent. Because it plugged straight into their existing Salesforce ecosystem, adoption was smooth and the early results helped secure funding for the next phase.

Conclusion: Smart AI investment is strategic, not arbitrary

So to wrap this all up, it's important to remember that the real question isn’t how much AI should cost, but how much value it should deliver.

When spend is tied to outcomes, leaders can show measurable improvements in efficiency, service quality, and citizen experience. Integration with platforms like Salesforce, MuleSoft, and Agentforce ensures that investment translates into real impact. Not just experiments.

And because every decision-maker has to answer to boards, regulators, and the public, we make sure programmes are built to stand up to scrutiny. Security, compliance, and scalability aren’t afterthoughts; they’re part of what makes AI investment strategic in the first place. That way, leaders can prove short-term wins while laying down a foundation that lasts.

At Infomentum, we help public sector organisations invest wisely, integrate effectively, and deliver results that matter. Whether you’re starting small through our Agentforce Jumpstart programme or planning wider transformation, we’ll help you build confidence, prove value, and scale success.

The public sector has always been about people - serving communities, protecting citizens, improving lives. AI doesn’t change that; it amplifies it. And collectively, we should be asking not just, “How much should we spend on AI?” but “How do we make AI work for our people and those we serve?” That mindset - outcome before outlay - is what turns innovation into impact.

If you’d like to explore what that could look like for your organisation, get in touch with us and let’s start the conversation!