We're reaching an inflection point with artificial intelligence (AI). This isn't the AI that pop culture has conditioned us to expect; it's not sentient robots or Skynet or even Tony Stark's Jarvis assistant. This AI plateau is happening under the surface, making our existing technology smarter and unlocking the power of all the data that enterprises collect. What that means: Widespread advancement in machine learning (ML), computer vision, deep learning, and natural language processing (NLP) have made it easier than ever to bake an AI algorithm layer into your software or cloud platform.
For businesses, practical AI applications can manifest in all sorts of ways, depending on your organizational needs and the business intelligence (BI) insights derived from the data you collect. Enterprises can employ AI for everything from mining social data to driving engagement in customer relationship management (CRM) to optimizing logistics and efficiency when it comes to tracking and managing assets.
A recent survey from Wakefield Research and account-based marketing (ABM) provider Demandbase polled 500 business-to-business (B2B) marketers and found that 80 percent of executives predict that AI will revolutionize marketing by 2020. The catch is, only 10 percent of marketing organizations are currently using AI. The survey pointed to integration (60 percent), training employees (54 percent), difficulty interpreting results (46 percent) and cost of implementation (42 percent) as the top challenges to devising and implementing an enterprise AI strategy.
Techcode's Global AI+ Accelerator helps incubate AI startups but also helps startups to incorporate AI on top of their existing products and services, and offers a consulting service to do the same for other businesses. I spoke to Luke Tang, General Manager of TechCode's Global AI+ Accelerator Program, who explained that Techcode covers AI application across enterprise, industry, and consumer apps. The accelerator sees some clear near-term opportunities for AI, as well as longer-term goals that are still three to five years out.
"Right now, AI is being driven by all the recent progress in ML. There's no one single breakthrough you can point to, but the business value we can extract from ML now is off the charts," said Tang. "From the enterprise point of view, what's happening right now could disrupt some core corporate business processes around coordination and control: scheduling, resource allocation, reporting, etc. These are very time-consuming tasks. Other opportunities on the enterprise side require more creativity and social intelligence that's not addressed by current technology. But we'll see this in the continued progression of AI over the next three to five years or so."
Tang explained how enterprises can leverage AI and laid out a step-by-step process to integrate AI in your organization. He also offered some handy tips and resources to ensure that your implementation is a success.
1. Get Familiar With AITake the time to become familiar with what modern AI can do. The accelerator offers its startups a wide array of resources through its partnerships with organizations such as Stanford University and corporations in the AI space. You should also take advantage of the wealth of online information and resources available to familiarize yourself with the basic concepts of AI.