AI readiness focuses on optimizing four key capabilities – People, Processes, Data, and Technology. How can having the appropriate tech – not just more of it – position you to make the most of AI?

To a degree, artificial intelligence (AI) can be considered a new piece of technology. But it’s much more complex than that: It’s a new layer of technology that, when correctly leveraged and supported, can open up new levels of insight and efficiency.

Therefore, it’s vital to understand the relationship between your company’s overall tech footprint and AI’s capabilities and needs. How does – or doesn’t – your technology stack up to provide AI with the complete, accessible information it needs? What do you need to implement, integrate, or optimize to help AI help you overcome today’s challenges, position you for tomorrow’s, and ultimately seize untapped value? 

Technology obstacles to AI success

The right technology tees up AI to deliver immense value. But many businesses still have a ways to go before they’re ready to put that synergy in place. 

“Legacy” is often something to be proud of, but not when it comes to technology. Legacy systems – SQL server environments, for example – aren’t optimized for AI. 

Acquisitions often come with their own myriad systems, leaving the overall organization with disconnected operations and cumbersome master data management, rather than the seamless infrastructure on which AI thrives. 

But organic growth (outside of M&A) can present its own tech challenges, exposing a gap between operational maturity and technological maturity. Companies may grow and evolve without maturing their tech stack – “If it works, why change it?” But they’re not the same company post-growth, and can’t keep operating the same way; the tech footprint that helped them scale up can’t keep up. For these companies, it’s time to operate at a higher scale, volume, and maturity – not only for AI, but to ultimately empower them to scale even further. 

Many businesses conflate automation with AI, but they’re different things. Invoicing, spend management, cash flow forecasting, and other processes can be automated; to best utilize AI, they must be. AI layers on top of data to look for anomalies, errors, and patterns that provide insights toward intelligent conversations; without established, automated processes to pull that data together, there’s nothing to layer AI on top of. 

The fallacy of the future tech state

Beyond the right technology, organizations need the right approach to technology, which includes an expansive, responsive, forward-looking perspective. 

Establishing growth goals based on a perceived future state makes for a sound business plan, but not an effective tech roadmap. That’s because with technology, there is no static future state – just an ever-moving window of maturity. You can build your technology around an ideal future state, but if your company is growing, you’ll outgrow that future state within a few years. So, your technology has to be dynamic, agile, and always evolving. Continuous improvement is needed to keep up with where the business is going.

Tighten up your tech readiness for AI

Consider these points as you move your tech closer to an AI-ready environment.

Clarify your use cases: How can AI advance your goals? 

The number of technologies promising to level up your operations seems limitless. Compounding this are several different approaches to choose from: an enterprise-wide platform, bespoke best of breed, hybrid. 

First, you have to start with the end in mind. You want to leverage AI, but for what?

• Access to data/insights faster, better, and cheaper?
• Measuring performance against key operational/financial KPIs and KRIs? (Key performance and risk indicators, respectively.)

Think specifically about potential uses cases for your industry. 

Say you’re a retailer facing inflated revenue numbers and excessive returns because online shoppers are buying extra sizes and returning items that don’t fit. More accurate sizing would mean more accurate orders, resulting in fewer returns. You can’t open stores for try-ons in every city – but an AI tool could use customers’ photos or videos to help them determine their correct size. That starts with technology that can handle, ingest, and synthesize that unstructured visual data. 

No matter your industry, consider and clearly define your use cases before trying to identify the right tech and the right approach. This first step also informs proper data readiness and process readiness.

Take stock of – then elevate – your current state

After you’ve brought your aims into focus, look at the state of your technology today. Is it capable of getting you to your desired future state? If not – and it probably isn’t – then you must fill that gap with the right solutions. This might require extra assistance for organizations not used to looking closely at technology, who might have limited IT capabilities and need specialized support to keep up with what they need.

Consider, too, that this also might require a mindset shift. New, different tech demands new, different ways of working, often a world apart from the way things have been done. Replace spreadsheets with dashboards. Instead of building dozens of nearly identical reports, develop capabilities to filter data sets based on specific needs. Adding a new AI layer to the same old processes won’t necessarily give you more efficiencies; it might just be a new distraction. You need to enhance those underlying processes, often with new tech solutions.

And as always, don’t lose sight of the human element. This technology advancement may also require retraining or upskilling your workforce. Focus on positioning your people to use AI to augment their work – not replacing them with it. Careful change management will be key.

Beyond the firewall, beyond borders

In readying your tech for AI, third-party risk deserves special consideration. If moving to a platform solution, you’ll likely be moving your technology into a cloud-based environment – and moving your data outside your four walls. Understand your providers’ protections and risks. Have you seen their SOC 1 and SOC 2 reports? Have they had data breaches? What safeguards and precautions do they have in place?

Also, if you’re a global company, be aware of any geopolitical or regional data privacy requirements that may affect you. Certain countries restrict data transfer across borders. In these cases, consider working with tech platforms that have sidestepped that challenge by establishing data centers within those countries.

Get your tech right to take your company into tomorrow

AI is new, now, and what’s next, all rolled together. Most businesses’ technology is not, and therefore not ready for AI. 

More so than shopping for solutions, companies need to focus on their goals and be clear on the outcomes they seek to achieve. Then, work backward from there by examining what technology is needed to bridge the gap between today and tomorrow. With the right technology in place, the foundation is set to set AI in motion and reap its full benefits.