Over half (52%) of U.S. companies accelerated their adoption of AI in 2021, and those that weave it into the fabric of every business operation will see the greatest success in coming decade.
Yet for many companies, the simple act of considering AI integration can be overwhelming. From the steep perceived costs to a lack of tech talent on staff, the challenges of adding advanced tools abound, especially for small and mid-sized companies. Yet, integrating AI has never been more important, since it can help alleviate labor shortages, boost productivity and even develop new products.
As the Chief of NASA’s Software, Robotics and Simulation Division, I oversaw a team of engineers that broke down complex robotics challenges into manageable elements, finding the ideal functions for which AI could be implemented to streamline processes. Today at alliantgroup, I have a firsthand look into the difficulties businesses face in integrating advanced technologies and help them find actionable ways to integrate AI.
By adopting the same mindset as NASA robotics engineers, any business can integrate AI tools to gain a competitive edge.
Leveraging advanced technologies at NASA
When NASA completed the construction of the International Space Station two decades ago, it represented an astounding achievement realized by humans and robots working in tandem.
NASA’s next challenge is to create a spacecraft that can be entirely built and deployed by robots, periodically visited by humans and left to run autonomously for months at a time. Automation is key to achieving this feat, enabling engineers to identify microscopic weaknesses in complex designs, mechanize processes that previously required human judgement, and enable the spacecraft to make precise adjustments by synthesizing and responding to shifting environmental factors.
In the same way, business owners can use AI to “steer” some of their own processes with little human intervention. Manufacturing companies can create their own autonomous plants akin to NASA’s latest space station, while small retail businesses, for example, could automate their bookkeeping processes and use AI tools to detect minute changes in customer spending that could affect sales.
Both examples rest on creating a digital infrastructure: a network of interconnected inputs that a machine learning algorithm can interpret and adjust or use to make decisions. Once a company creates a cohesive digital infrastructure, every event that could affect operations—be it a parts order arriving late or inclement weather affecting store attendance—will add to a data stream than can be monitored and tuned. Connecting factory production or retail sales to consumer forecasts, commodities markets and logistical systems will form a closed loop system ideal for machine learning, and an AI system can adapt to the subtle changes it monitors in these inputs.
Using NASA’s approach as a framework for automation
So, how can a business wary of embracing AI set itself on a path to integrating machine learning at this level? It comes down to thinking like the NASA team that built the autonomous spacecraft. By identifying key business inputs, determining the best way to monitor them and linking them together in a holistic view, business owners can derive specific insights to guide or even initiate their next move. At the same time, owners can use AI tools to automate time-consuming or rote processes.
For the factory, the key advancements for making this possible are digital sensing throughout the facility, electronic actuation of key process controls, networking of all such sensors and effectors, facility simulation and the ability to remotely inspect every inch of the factory. As opposed to building from the ground up, most of this automation technology can be added to an existing facility.
For the small businesses, changes to enable AI integration at this level could include finding a system currently in static operation that could be automated, or identifying key data that, if viewed holistically with other inputs, would be useful in making small but quick changes to operations for lucrative results.
Practically integrating AI tools
To effectively weave AI tools into a company’s workflow, the first steps a company should take include forming an AI task force, setting up a pilot project and focusing on sustainable integration.
An AI taskforce team should be comprised of people from a cross section of different disciplines within the company so they can more effectively identify key inputs necessary to create a holistic AI management model as well as processes eligible for automation. With a dedicated group of individuals focused on AI adoption, a business can stop continually delaying its implementation to focus on immediate needs.
Once the task force has identified improvement areas, they should weigh them against their revenue potential and factor in how disruptive a change would be while the kinks of automation are worked out. Choosing the right pilot project will help a company effectively integrate an AI-based system on the first try.
Finally, businesses should focus on sustainable integration from the start. This could include assessing the company’s capacity for extra data storage to accommodate new systems, initially focusing on solutions with the smallest physical footprint or required changes to the business’ physical environment (especially when it comes to automating individual tasks), and building infrastructure for company-wide education to extend the tool’s impact across all employees.
In practice, this could also look like a small retailer recruiting its head of manufacturing, business manager and IT specialist to form an AI task force, having them select the process of inventory management as an automation candidate, installing an AI-based management tool and finally educating all employees in the stockroom on how to use the program effectively.
It’s not rocket science, but it can look similar
The key to integrating AI tools into any business is to think like NASA engineers. When business owners can break down their key inputs, properly monitor them and link them together to form an autonomous model, they can step away from daily processes to focus more of their energy on the intangible business decisions automation cannot make. With a dedicated task force, a properly managed pilot run and a sustainable integration plan, businesses owners can start practically implementing AI tools to gain an edge.
As the world enters a new business climate, the ability to harness advanced technology will be crucial to achieve industry-leading success. To realize a company’s fullest potential, an AI algorithm might be its most important new hire.
