How AI Consultants Choose the Right Tools for Your Specific Business

Most companies get AI adoption wrong from the start. They see a flashy demonstration of ChatGPT in action or they hear that a competitor has just rolled out some new automation initiative and they jump straight on the bandwagon to start shopping for similar technology. In doing so, they’re solving for tools and not business problems.

AI consultants turn this entire process on its head. They’re not interested in selling you on one AI model over another. They’re not pushing what they know best. Instead, they start with something fundamentally more rudimentary – what’s broken in your company and is AI even the answer in the first place?

AI Isn’t Always the Answer

The first step of any reputable AI consultant is asking some hard questions. What processes are taking the longest? Where are frustrations continually cropping up? What tasks are employees complaining about the loudest (or at least covertly)?

This isn’t hypothetical figuring. Many consultants will spend days shadowing employees, seeing how their workday unfolds within your enterprise as opposed to how management perceives it’s unfolding. The difference between these two realities is often staggering.

And sometimes the answer is that AI isn’t even necessary. Maybe everyone is bogged down with data entry because no one thought to get the CRM and accounting platform talking to each other. This isn’t an AI problem – it’s an oversight. A good consultant will tell you to spend $5,000 on integration and save the $50,000 on AI solutions to address poor infrastructure.

Assessing Your Team’s Ability to Implement AI

Once a consultant has assessed where legitimate AI solutions may prevail, they’ll recognize something that far too many companies overlook – they’re own level of technical maturity. This has nothing to do with whether someone in your IT team is “smart enough” to handle it. It has everything to do with infrastructure, data readiness, and organizational willingness.

For instance, data infrastructure. Large language models need clean information with which to work. If your entire employee data exists in SharePoint folders, a million different Excel sheets, and Joe down the hall’s personal Dropbox because his mother taught him how to use it during COVID, AI cannot help you – it’s dead in the water. The consultant first needs to establish if you need six months of cleanup before AI can get off the ground.

The same goes for teams. A company with developers onboard could be running their own custom AI solutions for deployment. A company that’s lucky to have someone who can reset a password daily will need more copilot integration services, for example, to bridge the gap between AI solutions that work and consultant-made custom solutions.

The Build vs. Buy Decision Nobody Wants to Make

This is where a consultant earns their dollars. Whether it’s best to build or buy AI solutions. The answer isn’t straightforward from an outsider perspective.

If you rely on your competitive advantage upon specific processes that others cannot replicate through generic means, then a build is essential. For example, a pharmaceutical company with unique processes for drug discovery may be applicable to create custom models aimed at their certain areas of research. However, if you’re simply trying to crack a code to pay invoices like every other organization in the world, this custom development is throwing money away.

The math becomes complicated quick; minimums for custom AI projects start at around $100,000 and can go into the millions easily as well as annual maintenance covering 15-20% of the initial build cost. In contrast, software-as-a-service options run about $50 per user per month with minimal concerns for maintenance.

But those SaaS options come with their problems. They’re all created based on average scenarios meaning they’ll do 80% of what you need beautifully but they’ll fail miserably at the 20% that makes you unique. Consultants spend time bringing your specific processes in mind and mapping those against what tools actually do (not what their marketing tells you they do) to flesh out reality before picking a potential winner.

The Integration Option Vendors Don’t Want You To Hear

All too often vendors boast about their tools working well with everything else in the universe. Those shiny demonstration videos are not nearly as realistic when APIs don’t work per documentation, data formats need translating constantly and security protocols block half of what’s supposed to be working.

Consultants test these integrations before making recommendations. They’ll spin up a proof-of-concept environment and connect it to your real-life systems and see what blows up. They see this firsthand during testing before you’ve made any irreversible commitment and found it can’t access what it needs.

Furthermore, integration plays a role in tool selection that often isn’t considered but should be. An AI tool with less capability that integrates seamlessly will provide more value than a tool that takes months of custom integration and ramp-up time because time is money.

Taking Employees Into Account When Most AI Efforts Fail

Here’s what’s going to determine if your AI implementation succeeds: are people going to use it six months after implementation? Consultants who have seen multiple projects understand this and so they take user experience into account early on.

Some tools require extensive upfront training efforts while others lack all of the features but turn out intuitive out of the box – resulting in recommendations based on your workforce. If your organization has tech-savvy employees then an awesome (and perhaps steep) learning curve is acceptable; if your organization has employees with high rates of turnover and minimal tech training then a dead-simple answer even at the cost of effort may reign supreme.

Consultants also assess change management impact efforts – implementing something transformational may be worthwhile to justify hours spent providing support; sometimes it’s more valuable to apply less transformative tools in an effort to create limited destruction but operational value at 70% strength but 10% friction.

Looking Beyond Licensing Costs

It’s not just license costs that matter – AI tools require maintenance, revisits when it no longer works halfway through its expected delivery or you end up down-sizing and need something else altogether – costs that consultants help define before recommendations are made.

How much time will this involve from staff perspective? Do you have to hire others? What happens when the vendor realizes they’ve made a mistake and charges double? These operational considerations make all the difference in eventually determining competing options – an option that costs more up-front but substantially less on maintenance may make more sense than a cheap short-term solution that requires excessive amounts of an internal fee-based dedicated resource.

Delivering Recommendations You Can Actually Implement

The final recommendation isn’t a PowerPoint-filled presentation of whiz-bang AI developments on the cutting edge – consultants seek to meet you at your budgetary realities, technical restrictions and organizational potentials for staffing up/down.

Often times a consultant will recommend something smaller than you’d like – for example, beta testing one tool with one team instead of applying enterprise-wide transformation – allows mistakes to be made cheaply instead of running full steam ahead without professionals knowing what they’re doing.

Falling back on alternatives if the technology recommended doesn’t work out – and how you’ll migrate away from those solutions without losing out on months of work – rarely gets talked about during the sexy planning stages but becomes paramount when reality sets in.

The technology that’s right for your company is seldom what’s been marketed best or has eye-popping scores during demo days – they’re those solutions that meet your needs, work within other spaces, align with what your team can do and what deliverable value makes sense for the total cost of ownership. This is what consultants discover – and why their opportunities trump vendor pitches every time.