Forget the buzz about AI: ask the right questions first

Tom Bianculli at Zebra Technologies suggests nine things that organisations should find out about before investing in artificial intelligence technology

 

The world is changing fast, your instinct may be to simply react – especially when you either see mistakes happening or opportunities slipping away. However, there’s a difference between being reactive and being agile. A thoughtful and targeted response will enable you to eliminate wasteful spending, wasted time, and the problem itself.

 

Now, in business, there are things you can’t control, like inflation. However, you can adjust your information flows, workflows, and decision-making processes to ensure your employees, partners and other success influencers can “sense, analyse and act (on intelligence, not impulse)” when change – or trouble – is brewing.

 

Artificial intelligence (AI) is becoming an all-consuming topic in mainstream media right now, and discussions about generative AI and responsible AI are more than warranted. So, do your due diligence and understand how AI (machine learning, deep learning, etc.) can be responsibly used to help address your business challenges.

 

Injecting AI-based software applications into your tech stack to support automated information flows, workflows, and decision-making all the way to the edge of your operations can help your front-line workers deliver what customers want, when they want it, while running every aspect of your business efficiently.

 

The impact of your back-office employees – forecasters, planners, procurement and IT teams, and other admin-level advisors – in an increasingly data rich and complex world, is limited by the human brain’s ability to manually acquire, analyse, and drive the most optimised decisions, unless they have access to AI tools that can compensate.

 

However, assuming you’re not running a fully automated operation, someone will ultimately be making the final call on what action to take … people will continue to be in the loop. Therefore, the final outcome – whether the action that person ultimately takes is truly in the best interest of your business or customer – will depend on the depth and objectivity of the data informing their decision. 

 

In other words, it’s time to lean into AI-bolstered automation, no matter the technological maturity of your business – or the overall maturity of your business. Both startups and century-old companies are being held to the same customer standards and confronted by similar people and investment challenges. And low-tech systems can still be highly intelligent and highly impactful solutions as we’ve seen in healthcare, retail, manufacturing, and other sectors. 

 

If you’re wary of AI because of what you’re hearing as a consumer, it’s even more reason for you to study the technology from a business perspective so that you can ultimately “act on intelligence, not on impulse.” Organisations should therefore:

1. Understand what it really means to automate information flows, data analysis, workflows and decisions.
2. Learn how AI works in the framework of low-tech and high-tech automation – and how it learns to support your business most effectively. 
3. Talk to AI engineers, data scientists, and your peers to get both the technical and practical point of view on how AI works with information behind the scenes, with your team, with automation, and with the data generated by countless physical internet of things (IoT) objects, i.e., environmental sensors, mobile computers, data capture systems, machine vision cameras, RFID readers.
4. Make sure you’re clear on whether AI specialists are required to take advantage of a particular AI capability or if non-specialists can implement/manage the AI component you’re considering (or being asked to consider).
5. Confirm if you need additional tools to democratise the software so everyone can work with/create AI-based solutions.
6. Verify how long it will actually take to create, test, and deploy the AI-powered tech stacks you or your advisors believe can effectively solve your problem.
7. Ask about how AI is controlled with respect to security and privacy in the context of your intended use case.
8. Investigate the differences between generative AI and “purpose built” AI for specific front-line or back-office business applications.
9. Appreciate why AI, even with its immense intelligence capabilities, is not a “silver bullet” but rather an active ingredient in the solution you’re formulating for each problem. Like all other technology, it must be implemented in accordance with policies and procedures that best serve the end-user.

Instead of making a decision based on familiarity, convenience, up-front cost, or compulsion, challenge yourself to stop and scrutinise what’s happening and why it’s happening. Then study all your options, constantly asking “why” something is best (or not).

 

Challenge others to do the same and dig in a bit when someone seems to either want to jump too fast or delay too long. (Remember, technical debt is not something you accrue only by making the wrong purchases. It’s something that will quickly build when you wait too long to replace underperforming technology.). Then, once you’re confident you have the right technology in place, be sure you commit the effort to the required change management. 

 

Remember, technology’s value is derived from its ability to help people work more efficiently, make better decisions, and adjust quickly as customer expectations and market pressures change.

 

So, if you want to maximise your return on investment, make sure your technology is configured in a way that fully supports your team – and make sure your team understands how technology can help them. 

 

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Tom Bianculli is CTO at Zebra Technologies. Could AI be useful to some of your teams? Read about the potential of machine vision here and Workcloud here

 

Main image courtesy of iStockPhoto.com