AI & AR: a duo evolving in the industrial sector

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The full potential of assisted/augmented reality (AR) and Artificial Intelligence (AI) in the industrial workplace has been a topic of interest for some time. Accenture found that found nine out of ten C-suite executives believe they must leverage AI to achieve their growth objectives. In fact, research also revealed that implementing AI in the supply chain can allow businesses to generate $1.3-$2 trillion per year. Further to this, the global AR market size is expected to reach 8.8 million units by 2026, with smart glasses experiencing increased adoption in various sectors including logistics.

The most visible examples of AR have been in the consumer sector, unsurprisingly. From games like Pokémon GO to showrooms in IKEA, consumer uptake of these technologies has been swift and widespread. But industrial applications in logistics have been growing too – in many cases, more rapidly. Since 2020 in particular, with travel all but impossible, remote work a necessity, and budgets squeezed, industrial and logistics applications for AR/AI became less of a nice-to-have, and more of a need-to-have.

This is unlikely to change. Even after the pandemic runs its course, it’s likely many logistics businesses won’t want to revert to old methods. Reality has changed irrevocably, and with it, the advantages of implementing AI and AR solutions have gone from being merely aspirational to almost essential. Because these technologies do one thing really well – they enable efficiency in an age of disruption.

 

What are the technologies?

Let’s take a look at the technologies in turn. Assisted and Augmented Reality (AR) are often used interchangeably, but Assisted Reality, unlike Augmented Reality, doesn’t change what the user is seeing. Rather, it adds an extra layer of information into their peripheral vision. Assisted Reality can be in the form of something like smart glasses, while Augmented Reality would often completely obstruct your view of what is actually around you. Indeed, smart glasses are one of the top applications for Assisted Reality, with adoption not only anticipated to grow in the coming years, but also to accelerate as spending starts to transition away from mobile AR and towards head-worn AR.

AI, on the other hand, has the potential to completely transform the logistics sector. McKinsey found the logistics industry mostly adopted AI for four business functions, which include: service operations, product and service development, marketing and sales, and supply chain management. Its growth is happening just as quickly globally and being such a significant enabler for the next wave of technologies, this growth is likely to become exponential.

 

What does this mean?

Tasks like retrofitting, assembling, manufacturing, and repairing production lines are perfect for AI and AR. For example, the ability for AR to provide anyone from an auto engineer to an astronaut with a visual overlay (such as with smart glasses) for information on what they’re looking at has been a core promise of the technology from day one. Vehicle makers and logistics service providers have been prompted to investigate the potential of this technology, with BMW already providing display rigs for maintenance and allowing customers to preview different models and configurations of cars in their virtually landscaped driveways.

In warehouse and logistics, we can envisage manufacturers increasingly using AI to increase capacity and accuracy too. Automating tasks such as pallet preparation, for example, can help ensure customer orders are packed correctly and eliminate scanning.

AR assistance also provides numerous benefits, including a reduction in time in interpreting instructions, reduction in training time and increase in productivity. Our own research found that 57% of logistics businesses are likely to deploy smart glasses within the next three years, with 47% doing it for hands-free functionality, 47% for improved on-site capabilities and 40% for improved mobile working. Indeed, Gartner predicts that by 2026, 75% of capital-equipment-intensive industries will use AR as a key component for cost reduction/avoidance among frontline workers. Gartner also found that an AR-Assisted Assembly use case achieved the following results using AR in aerospace assembly:

  • 90% to 99% reduction in time interpreting instructions (“time to information”)
  • 85% reduction in training time
  • 40% increase in productivity
  • 35% to 50% reduction in overall technician time

 

Challenges…

The challenge of deploying evolving technologies, is always that until they have fully matured, integration can be a challenge. With smart glasses as well, there can also be security and privacy concerns. AI can help here. Given that operational technology environments produce huge amounts of data and security logs, AI can be deployed to sift through the noise and assist by automatically detecting intrusions, malware, and unfamiliar employee behaviours to protect organisations and supply chains. That said, while AI is a more developed technology, AI is also costly, and may require a strong upfront investment. Finally, AI can be hard to scale up and down. Gartner found CIOs and IT leaders are finding it difficult to scale AI projects, with only 53% of projects making it from prototypes of production as they lack the right tools to create a production-grade AI pipeline.

 

…But not setbacks

However, these problems are likely to be minor blips at best. It doesn’t mean deployment is impossible or even difficult. Firstly, investments are a necessary part of business growth, and most business leaders within the logistics industry agree that AI and AR promise excellent investment returns after only a short period of time – when deployed correctly. Bosch Czechia for example, recently installed a Dynabook Smart Glass solution to enhance productivity and efficiency in their technical department, particularly for electricians for use in maintenance support. The devices proved such an asset to the team that they are now investigating other applications and use cases.

Secondly, AI, AR and devices like smart glasses have grown far faster in the logistics sector than consumer, despite more widespread use in the latter. Traditionally, devices that gain popularity through business use are always a little slower to take off and gain visibility. While global spending on AR and VR headsets, software, and services, including purchases by consumers, rose to $12 billion in 2020, the majority of this growth was in the business sector. As it slowly starts to become more popular with consumers too, this trend is likely to pick up speed. With the pandemic accelerating the opportunity to demonstrate their value, AR and smart glasses may continue to gain ground thanks to their promise of lower costs, greater safety, and better learning retention. Growth doesn’t need to be immediate in order to be recognised.