There are many different catalysts that might cause a business to move to the cloud or change the apps they use [if they’re already operating within a cloud-based system]. That said, a number of common themes usually appear including the desire to streamline solutions, improve internal efficiency, and save costs through appropriately leveraging automation.

Heading into 2026, those drivers are still front and centre, but the tools have evolved. Cloud apps, automation and data are now sitting alongside artificial intelligence [AI] and machine learning, which are quickly moving from ‘nice to have’ to ‘business as usual’ for many businesses.

 

why new tech doesn’t always stick

 

This ongoing push for new tech is usually championed by a key individual or individuals—but that doesn’t necessarily mean that these technological changes and improvements will stick in the long term.

You can’t simply implement a solution, invite a number of users then hope that it’ll work out exactly as intended. Often this approach has the exact opposite result and projects can end up having to be abandoned in their entirety.

There’s no doubt this is a huge waste when so much time, effort and money has been invested in a project.

To effectively make technology stick in the long term you need:

  1. appropriate research, and
  2. effective implementation.

AI is the latest wave of “must-have” tech landing in businesses, and it comes with all the same risks [plus a few new ones]. The principles for making technology stick haven’t changed, but the stakes are higher. That’s why it’s worth asking a more specific question: is AI actually ready for your business?

 

is AI ready for your business?

 

For most businesses, the answer is: AI is ready in some areas, not in others – and the trick is knowing the difference. Tools that help with drafting content, summarising documents, analysing patterns in your data, predicting cashflow, or automating routine workflows can already deliver real value. On the other hand, handing over critical decisions to AI without checks and balances, or expecting it to fix broken processes, is still a recipe for pain.

The approach we’ve taken is simple: start with your strategy, not the tech. Understand the problems you’re trying to solve, then look at where AI can augment your people and your existing systems – not replace them.

 

making new tech stick: the step-by-step process

 

Follow the steps listed below to help maximise your chances of successfully introducing new technology within your business.

 

1. get demos from the professionals

Don’t just rely on online videos and try to work everything out for yourself. Chances are, you’ll learn far more by speaking to representatives from the technology provider itself—so sign up for a proper demonstration where they can take you through the tool’s end-to-end functionality and answer all your queries.

 

2. ask as many questions as possible

I’m sure you’ve heard of the phrase “There are no dumb questions”. So try and ask every question that you have about the solution, even if you think you might know the answer—it’s always best to know for certain. It might be a good idea to brainstorm potential questions before your demo call just so you can be sure that you don’t miss anything.

For AI tools in particular, add questions around:

  • where your data is stored and who can access it
  • how your data is used to train the AI [or not]
  • what controls are in place around privacy and security
  • how you can review, override or roll back AI-driven actions

 

3. make use of free trial periods

Most tech solutions have a free trial period but even if they don’t, I suggest you ask for one. When you sign up for the free trial, make sure you do it at a time when you’ll actually use the product. For example, don’t sign up over Christmas or when you’re on holiday. Give the solution an appropriate amount of time and attention so that you can really get used to it; this is critical in working out if it’s right for your business.

 

4. get feedback from your peers

Social media allows you to connect with other people in your industry or sector all around the world, and practical feedback on how they’ve found a product.

There’s a multitude of Meta and LinkedIn groups you can join to get an ongoing stream of product reviews, recommendations, and more. Take advantage of these to read everything you can about a product before making a purchase decision.

 

5. purchase the right subscription levels

Most technological solutions have multiple subscription options according to the levels of functionality they offer. However, most people also want to save costs. If there’s a subscription level that best suits your needs but is not necessarily the cheapest option, it’s still probably the best one for you. Remember that if this is implemented correctly, you should be saving money anyway by having better internal processes, becoming more efficient, and automating time-consuming work.

With AI products, “free” or very low-cost tiers can be tempting, but they often come with limitations around data controls, security, or integration. For a business environment, it’s often worth paying for the level that gives you enterprise-grade security, admin controls, and proper support – especially if you’re dealing with sensitive client or financial information.

 

6. make sure that your apps integrate

If automation and efficiency are your goals [which they should be], then you need to make sure that your apps all talk to one another. Gone are the days where you use only one piece of software. Chances are, you’ll have multiple apps in your tech stack—and these should all have a level of integration that, at a minimum, means they share the same client database. If you have to consistently re-enter the same information in multiple places, not only will you lose your efficiency gains from the cloud, but you’ll also run a greater risk of error. In an ideal world, they’d also go one step further, and each app would be able to trigger workflows and processes in other apps too.

AI performs best when it can “see” relevant, accurate data across your systems. When reviewing integrations, think about how your AI tools will connect with your practice management, accounting, CRM, and document systems. The aim is to avoid creating yet another data silo labelled ‘AI’ and instead embed AI into your existing tools and workflows.

 

7. assign an internal champion[s]

This person will learn all they possibly can, so they understand the product inside out. They’ll be the go-to person within the business who will not only make sure that the app is working but that it’s also being used properly. If your team is large enough then I’d suggest you have a different person for each app otherwise, someone might become overburdened with their role as the resident ‘tech guru’!

 

8. train your team and bring them on the journey with you

Don’t let your team fumble through by themselves. Make sure they get the training they need to properly use the technology and ensure they understand why it’s important, explaining the many benefits that it can offer. Include them in the decision-making and implementation processes. Inclusion and education are the two core pillars behind ensuring that the technology is widely [and correctly] used—so make sure you don’t neglect them.

With AI, training needs to go beyond “which buttons to press”. Your team needs to understand:

  • what AI is and isn’t good at
  • how to review and sense-check AI outputs
  • what data they can and can’t put into AI tools
  • how AI will change their roles [ideally freeing them up for higher-value work, not replacing them]

 

9. if it’s a big change, hire a professional

If you’re undertaking a wholesale overhaul of your systems and you don’t have the right technical expertise in house to get it all working properly, engage an integrator to get the job done.

There’s no point in making a mistake. This will only lead to frustration, delays, and rising project costs.

 

10. get intentional about AI in your tech roadmap

AI shouldn’t sit off to the side as a one-off experiment; it should be considered as part of your broader tech and business strategy. As you review or refresh your tech stack, ask:

  • Where are our biggest bottlenecks or pain points today?
  • Which of those are suitable for AI to support or automate?
  • What are the risks – to data, clients, compliance, and culture – and how will we manage them?
  • How will we measure the impact of AI [time saved, errors reduced, turnaround times improved, new services enabled]?

 

remember: technology is always changing

 

Technology is ever-evolving. That’s a given. While constant change is disruptive and to be avoided, you also have to remember that it’s important to stay as nimble as is appropriate for your business.

Don’t be afraid to try new things. However, balance this with common sense. App overwhelm can end up confusing and annoying for your team, significantly damaging their productivity, so don’t just plump for every shiny new solution that lands in the app marketplace.

AI is no exception. New AI features and tools are being released almost weekly, but that doesn’t mean you need to chase all of them. A small number of well-chosen, well-implemented tools will beat a messy collection of half-used apps every time.

 

know when to move on

 

When adopting a new product, make sure there’s always a well-defined exit plan for the technology that you already use [e.g. how to export features and perform backups]. If you ever outgrow something or realise that it’s just not for you, don’t hang onto it for too long—this will just cost you more in the long run.

As you introduce more AI into your business, also build in regular reviews: are the tools still delivering value, are they still aligned with your strategy, and are the risks still acceptable? Treat AI like any other part of your tech stack – it has to continually earn its place.

 

need a hand?

 

If you are thinking of moving to the cloud or changing up your existing tech stack and want to have a chat with the experts about how to best make it stick, contact our digital advisory team here or give us a buzz on 1300 BDEPOT.

 

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Originally published 8 April 2021.