AI, together with VR and AR, is changing the business environment by introducing new challenges and breakthroughs. While this holy trinity is a driving force in business, their primary functions are distinct.
For instance, AI and VR are sisters with different technologies behind them and are primarily used in distinct industries. AI mainly focuses on task automation and data predictions, especially in fintech, where it uses machine learning models to predict the behavior of loan portfolios.
Nevertheless, AI, AR, and VR have something in common: they are programmed to increase business efficiency and reduce costs in manufacturing industries. This is what we explored in Part I of this series, breaking down five ways businesses can implement AR, VR & AI.
Now, we continue the narrative and pick up where we left off. Specifically, with those benefits laid out, what are the challenges and constraints standing in their way? These are critical aspects for businesses to internalize and anticipate so that they know where the land mines are buried.
Then, finally, we synthesize all the pros and cons and examine if these implementations are worthwhile, and how they should be navigated. Let’s dive in…
Challenges & Constraints
Like any other technology, AI, AR, and VR have constraints that could slow down business development. Here are a few…
1. Technical Challenges
Technical issues and costly maintenance are significant constraints in developing and implementing tech solutions. Expertise and specialized knowledge are required, and maintaining servers, hardware, and devices can be expensive for starting companies.
For instance, if you put an AR mirror that helps customers to try on clothes in your retail store virtually, it needs maintenance. So, you not only spend money on the equipment but also on the labor.
OpenAI from ChatGPT was an expensive toy, yet Microsoft covered its costs for server maintenance. It practically bought it and provided it with the needed infrastructure.
2. Data Security
Data security is also a potential drawback in AI, VR, and AR processes, as the technologies operate with large amounts of data. It needs to be clarified how to store, process, and share it correctly according to the laws.
In Europe, for instance, there is the GDPR, which businesses have to follow. So you need to know a proper approach to how to adapt data to it, including storing and sharing it and acting under regulations.
3. Limited Technological Growth
While the speed of technological growth varies from industry to industry, AI, AR, and VR have scalability limits as they primarily perform a particular task, such as analyzing data by financial model.
If you need to train AI for a different model or date, you have to write the code from scratch, but this is another story that involves machine learning.
4. Lack of Standardization
Data exchange needs to be more standardized within AI, AR, and VR since every project is built on its infrastructure without API integrations. Everyone has different products in distinct words; nothing is united.
It makes integrating products from different manufacturers difficult because it is impossible to do so simultaneously. There is no flow, as in putting Lego pieces together individually.
So the question remains: do we really need forward-thinking technology when it comes with a slew of drawbacks that stymie progress?
Do You Really Need It?
Nothing is perfect, including AI, AR, and VR. Yet, the industry is trying its best to solve the potential problems and prevent them from happening with the help of the tool that would ease the implementation process.
A few tools could make it happen – it depends on the industry and specialization, as such devices act like technical screwdrivers for highly unique screws. This is the reality of today.
For example, on Product Hunt, you can find over 100 tools in high demand: ChatGPT and its Open AI, the image-to-text recognition system, and other applications based on the company’s technology for the past week.
Yet, before using any of the tools, you must understand which problems you have to solve and, based on this, match the best technology in terms of execution, implementation cost, or ROI. Using the tool because it is in trend is also not the best way to hack the business system; it would only work in some cases.
Some analytical tasks are easier to keep on the servers. However, it depends on the amount of information due to the costly maintenance of this technology. Companies with big data might find servers handy, yet they should consider that there are only a few implementation specialists in this field.
Despite much discussion about AR and VR, the execution process is still developing, and only a few specialists know how to do it from start to finish. Incompetence may arise when big businesses buy out these specialists, making it unrealistic for startups.
Implementation of AI, AR, and VR in the Business Ecosystem
Implementing AI, AR, and VR is possible today, and you just need to understand the industry standard, business model, and goals. The best way to start with implementation is with a standardized approach, from defining the problem to creating a solution.
Understand Business Aims
In e-commerce, reducing costs is a significant concern, and startups use VR to address product return issues. AR, like virtual sneaker try-ons, can also solve these problems. Understanding the business goals and the problems the technology solves makes it easier to decide on implementation.
Which Issue Does the Technology Address?
When you determine your business goals, the next step is to understand the potential of the technology and its probability of solving the problem. You could reduce employee costs, attract new audiences, cut other expenses, and increase the ROI by understanding technology’s effect on the future of the business.
The final step in technology implementation is cost estimation, including hiring specialists and integration switching. It requires significant time and resources, with maintenance costs reflecting the number of clients. Before implementing AI, AR, or VR, consider the economy, investment risks, and ROI.
What is the Future of AI, AR, and VR?
AI and AR/VR will have widespread applications. AI will be used in various industries and may even be integrated into the human brain. The global AI market is expected to reach $267 billion by 2027. Advances in technology will decrease infrastructure costs and introduce new processing chips.
The exact development of these technologies is uncertain, with everything centered around AI, textual, and visual intelligence. The creative industries will use AI, while people will focus on physical tasks.
Sergey Vart is CEO & co-founder of Eyebuy.me
Header image credit: fabio on Unsplash