Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Almost every confidential investment memorandum (CIM) for a tech-driven enterprise includes the company's mention of artificial intelligence (AI) or machine learning (ML) capabilities. But as with other investment buzzwords -- such as "subscription revenue" -- there is a tendency to use AI or ML to suggest complex, business-enabling, proprietary technology and processes to distinguish the offering as differentiated or technologically superior. This is often to garner higher valuation. We've all heard examples of AI failures that make for good headlines and provide interesting cautionary tales.

Artificial intelligence technologies have reached impressive levels of adoption, and are seen as a competitive differentiator. But there comes a point when technology becomes so ubiquitous that it is no longer a competitive differentiator -- think of the cloud. Going forward, those organizations succeeding with AI, then, will be those that apply human innovation and business sense to their AI foundations. Such is the challenge identified in a study released by RELX, which finds the use of AI technologies, at least in the United States, has reached 81% of enterprises, up 33 percentage points from 48% since a previous RELX survey in 2018. They're also bullish on AI delivering the goods -- 93% report that AI makes their business more competitive.

Yara, one of the world's leading fertilizer companies and a provider of environmental solutions, have created an industry-wide business platform to connect and empower independent farmers. It will use IoT sensors and AI and TWC to provide hyperlocal weather forecasting, crop damage prediction and real-time recommendations. Already downloaded by over 1,300,000 farmers, this platform is transforming existing supplier relationships and expanding its value. Yara built a digital farming platform that connects and empowers independent farmers, expanding its business model as a first-of-a-kind, competitive differentiator in the industry. Yara, one of the world's leading fertilizer companies and a provider of environmental solutions, have created an industry-wide business platform to connect and empower independent farmers.

Business Intelligence, Reporting & Analytics have been central to Asset Manager marketing efforts for years. Now, Advanced Analytics and AI are increasingly playing a role across Sales & Marketing operations. For example, Microsoft has incorporated AI capability into its Office 365 product suite. Similarly, Microsoft's social network/ business development platform – LinkedIn – centrally manages its machine learning models with a homegrown "AI Automation" platform named "Pro-ML". Salesforce will accelerate its AI/ML/data effort with its recent acquisition of Tableau Software.

San Diego-based parcel consultancy Shipware LLC said this week it has introduced proprietary machine-learning software, Krystal AI. The company said this offering will augment operations and optimize carrier pricing by providing its customers with insights and data points culled through a combination of factors. "Krystal AI is the culmination of tens of thousands of data points and hundreds of years of carrier pricing expertise," said Rob Martinez, Shipware president and CEO, in an interview. "Driven by'next generation' needs of high volume shippers, the tool has been many years in the making." In terms of the benefits Krystal AI provides shippers, Martinez said it dynamically rates actual shipping data given theoretical inputs – like a specific improvement in a series of accessorial charges, or an improve dimensional divisor, lower minimum charge, rate cap to GRI's, etc.