Whether you’re a vendor or service provider, you face certain challenges when it comes to artificial intelligence (AI).
Driven by data, the internet of things (IoT) and the power of cloud, AI is simply defined as intelligence demonstrated by machines. However, it’s common to see AI promoted as an essential part of a product or solution even though AI may be only a small component.
While AI is still in its early stages, the technology is poised to play an important role in connecting people, networks and data—especially with the help of cloud. In fact, Gartner reports the business value of AI is projected to reach more than $3.9 trillion within the next five years. So, whether you’re a vendor or service provider, it’s important to determine how and when to incorporate AI into your solutions.
AI adoption and growing pains
While businesses are eager to deploy AI, they face several challenges. First, AI is still fairly limited. Developers are working to teach AI to complete basic tasks, which is a critical step, but the technology has a long way to go. Despite how movies portray it, AI does not automatically equal super-intelligent, sentient beings.
Integration is another obstacle for AI adoption. Currently, no generic and easy-to-deploy AI solutions are available in the marketplace. Without standard compatibility, AI integration requires a highly customized and detailed approach.
Deciding when to incorporate AI represents yet another challenge. If you’re a solution provider that uses AI to automate too soon, you risk alienating customers who aren’t ready to adopt it. On the other hand, if you’re too slow to incorporate AI-based technologies, you risk being outpaced by your competitors.
Two big predictions for AI
The opportunities AI offers, especially coupled with cloud, could lead to unprecedented levels of productivity, efficiency and innovation. Here are a couple predictions on how AI will evolve with the use of cloud technology.
- Prediction #1: Investment in creating specific AI solutions will increase
We’ll likely see the building or training of AI for a specific function. For example, a business will use AI and cloud to manage a warehouse for increased efficiency, control and visibility. These practical AI solutions for businesses—built from the ground up with the cloud in mind—seem more realistic than the fictional, all-knowing and all-controlling AI seen in movies.
- Prediction #2: Businesses will train AI to deliver services
Companies will train AI to deliver services such as data analytics. Data helps drive smarter AI, so why not create AI to tap into data analysis at fast speeds? Possible real-world examples include making complex predictions with long data sequences for language comprehension, climate modeling and weather prediction.
Investing in AI’s future
The success of AI will depend on companies building the right AI-enabled solutions for real-world applications and use cases.
For its part, Ingram Micro Cloud is making significant progress in securing investments to create the future of AI. For example, in October 2018, they announced a new distribution relationship with NVIDIA, a world leader in AI computing technology. The partnership with NVIDIA opens the door to this and other opportunities for Ingram Micro Cloud and its reseller community to sell IoT and AI solutions.