Oh Right: AI is just another tool
(a reality check on AI adoption)
Let’s be fair dinkum for a second: you can’t scroll through LinkedIn or open a tech newsletter these days without being absolutely bombarded by AI pressure. It’s pitched as the ultimate silver bullet, the magic wand that’s going to do your taxes, brew your morning flat white, and completely run your business while you kick back.
But sitting through a presentation at a recent Melbourne Salesforce User Group (25 June 2026), a massive truth bomb dropped that made us all go, “Oh, duh.”
AI is not a magical entity. It’s a tool.
And an AI project? It’s just another IT project.
Cati Vescovi presenting Bridging the AI Execution Gap at Melbourne Salesforce User Group
Lately, the bottleneck in business hasn’t been a lack of ideas. AI has given us an absolute abundance of those. The real bottleneck now?
Execution.
We’ve shifted from imagination to delivery, and that means we need old-fashioned ownership, governance, critical thinking, and measurable outcomes.
Fresh data backs this up, too. The 2026 AI Operations Report by Coastal and Oxford Economics (surveying 800 business and tech leaders) highlights a massive “Execution Gap.”
While 84% of leaders believe AI is making them more competitive and 74% are actively increasing their investments, the actual implementation is stalling hard.
Why? Because employees are ready for AI, but most AI systems simply aren’t ready for them. In fact, 73% of organisations are still hitting brick walls when it comes to user adoption.
If you’re feeling the executive pressure to push AI into your business, especially if you’re trying to connect your front office with your back-office financial systems, here is a candid reflection on what it actually takes to succeed.
What Actually Determines Success?
One of the most grounding frameworks shared at the user group was the Boston Consulting Group (BCG) rule. When you look under the hood of a successful strategic adoption, the breakdown of what drives value might surprise you. It’s not about who has the flashiest algorithm. It looks like this:
- 70% People and Process: organisational adoption, change management, and governance.
- 20% Technology and Data: Infrastructure and information quality.
- 10% Algorithms: The actual technical foundation.
(BCG, 2024)
The takeaway: A whopping 70% of your success hinges entirely on your people and your processes.
Most AI value is realised through people and process change, not features alone. The 2026 Coastal and Oxford Economics report echoes this perfectly, revealing that 50% of leaders admit users don’t trust AI outputs enough to act on them, and 46% say the outputs just don’t fit real-world workflows.
As one Chief Digital Officer in the report put it: “We spent more time on the idea on paper and less on how AI would actually work day to day.”
If your core business workflows are a bit of a pigsty, throwing automation at them will just give you a highly automated, lightning-fast pigsty. The classic discipline of business analysis never goes away. You still have to ask:
– Why do we need all these steps?
– Is this workflow actually necessary?
Where AI Actually Shines: Meet Your New Assistants
When we look at where AI is making a genuinely positive, safe, and practical impact right now, we have some fantastic examples, like the reimagined AI Slackbot.
Instead of forcing your team to navigate between a dozen different browser tabs just to find information, tools like Slackbot bring AI right into the flow of where work is already happening. You can literally chat with your assistant in plain English to pull an account history, summarise a long thread, or query your Salesforce CRM data on the fly. It moves AI from a lonely “single-player” tool into a highly cooperative team assistant that takes the friction out of everyday operations.
However, AI can still be confidently wrong if left completely to its own devices. If you ask it to build financial workflows or write code without understanding the underlying logic, it will hit limits. To be a great prompt engineer, you need that foundational business knowledge to know when the tool is feeding you rubbish. Critical thinking and deep process knowledge are still your ultimate superpowers.
Systems Before Tools: Reimagining the Path
It’s incredibly easy to approach AI backwards. The “Wrong Path” is a loop we see all the time: buying the Tools, getting blinded by the shiny Features, watching tech Demos, and only then looking around for a Problem to fit it into.
The better path? Start with the problem.
AI amplifies both excellence and chaos. Instead of asking “How can AI help us?”, the strategic approach is always to ask “What business problem are we trying to solve?”
Capability vs. Readiness
There is a massive difference between what a tool can do and whether your business is actually ready to do it. Sure, AI can assist, summarise, and automate. It has the technical capability.
But are you operationally ready? True readiness means checking off the foundational pillars:
- A clear strategy and engaged leadership.
- An aligned culture with skilled people.
- Effective processes and strong communication.
Don’t let messy data put a complete stop to your progress either. Your data is never going to be 100% perfect. The trick is to find ways to clean and stabilise your data over time, rather than waiting for a perfect state that doesn’t exist. Stabilise before you scale.
The Practical Path Forward for Finance & Operations
At Swan, our bread and butter is linking the front office to the back office using Salesforce, Mission Control, Accounting Seed, and StoreConnect. We care deeply about the entire lifecycle: From the moment a customer clicks ‘buy’ on your storefront to tracking project milestones, all the way to the final ledger entry.
If you want to pull advanced automation into that financial ecosystem, stop focusing on the hype and look at the practical journey toward scalable value:
- The Idea & Pilot: Focus on small pieces of feasibility first. Start with a tiny, low-risk workflow to test the waters before going all in.
- Adoption & Iteration: Manage your team through the change so they actually trust and adopt the tool. If a pilot project reveals gaps and doesn’t quite come up to scratch, don’t scrap it. Tweak it, recalibrate, and iterate until it aligns with real-world workflows.
- Scale: Only scale what has been stabilized and proven to show measurable outcomes. By ensuring the foundation is rock-solid first, you guarantee long-term adoption and genuine return on investment.
Don’t let the pressure to innovate force you into a tech investment you aren’t ready for. Keep your eyes on the business outcome, look after your people through the change, and the technology will do the rest.
Want to connect your front-office sales with your back-office finance without the fluff? Let’s chat about making your processes right as rain. Get in touch with the team at Swan today.