It happened recently as I was looking at demonstrations of two very interesting new technology-based companies that help automate due diligence processes. They are both classic examples of the type of technological innovation that's happening at lightning speed in the legal industry today. They are addressing an enormous pain point in the industry: the mind-numbing burden of manually reviewing thousands of contracts as part of a due diligence mandate. It's the kind of work that has provided a good living for generations of young law firm associates, but it is not efficient and, being human-based, not always very accurate. These two new companies are using technology to make that review more efficient and accurate, by analyzing, summarizing, and extracting structured data from big masses of unstructured and wildly inconsistent documents. To the extent the technology works, it's because it imposes some kind of order on the non-standard work of human lawyers.

Matt Coatney is a technology executive, business advisor, entrepreneur, author, and speaker. His focus is on bringing advanced artificial intelligence and analytic technologies to market. He has co-founded three companies, advised several others, and contributed to the early success of two different tech startups. Matt has also launched data analytics products designed for the fields of life sciences, healthcare, government, finance, and law. Currently Matt is the VP of Services for Exaptive; he previously was the IT strategy lead for global law firm WilmerHale, and was in charge of technology and operations for a legal search product at LexisNexis.

Build Cool AI Technology in 90 Minutes and Learn by Doing (No Coding!) If you're reading this, you probably know that, arguably, artificial intelligence is the most significant technological developments of our time. There will be people who are able to use AI to do incredible things and others who watch technology and the world change around them at a blistering pace without understanding fully what's going on. If you're someone who stays "in the know," you need to learn about AI. We think that you can best learn by doing.

The adoption and application of Artificial Intelligence (AI) continues to accelerate at an exponential rate in modern businesses. As referenced in the 2017 Tech Trend Report, AI is nearing completion of the next layer in technological advancement, integrated into everything individuals and organizations do. This trajectory is predicted to drive cumulative worldwide spending of $40.6 billion on AI projects by 2024 – according to Raconteur. This is expected to create mass opportunity for the pioneering businesses currently investing in AI development. Moving beyond the hype in existing media coverage, this post will uncover the reality behind what AI means for businesses today, in the near future, and beyond 2017.

Watson captured the public imagination about artificial intelligence after defeating two world champions of Jeopardy in 2011 and bringing home a $1 million prize. Since then, Watson has gained new cognitive capabilities through APIs like Alchemy (for sentiment analysis), Tone Analyzer (for personality and emotional analysis), and Conversation (a chatbot builder) and has been embedded in hundreds of applications across financial services, healthcare, retail, and digital. "Chances are, you've interacted with Watson without realizing it," says Alyssa Simpson, Program Director at IBM Watson. "Many companies hide their use of the technology for competitive reasons. They don't want a competitor to buy it too."

Less clear was how a new IBM partnership will change Salesforce AI plans. What's the state of Salesforce Einstein, the portfolio of artificial intelligence (AI) capabilities announced last fall? Salesforce generated plenty of media coverage this week with two big announcements. Here's my take on the realities of a partnership with IBM and what we have yet to understand about the packaging and pricing of Einstein. The first announcement from Salesforce this week was the unexpected bombshell on a new partnership with IBM that headlines simplified as "Watson meets Einstein."

The two artificial intelligence products from IBM and Salesforce, respectively, are being brought together as part of a new partnership between the tech companies. Besides creating a tag team named after two familiar characters from literature and science, the AI partnership is designed to help retailers crunch a broad variety of data -- including customer shopping preferences, weather data and industry information -- to boost business. By combining local shopping patterns, weather and retail industry data from Watson with customer-specific shopping data and preferences from Salesforce Einstein, a retailer will be able to automatically send highly personalized and localized email campaigns to shoppers. IBM is also making weather data available to Salesforce customers as a service, to help them analyze how weather events impact their business. This new partnership comes after IBM acquired huge Salesforce partner Bluewolf Group, with Salesforce CEO Marc Benioff's blessing, a year ago, reportedly spending $200 million on that deal.

One area of business that stands to benefit from machine learning is customer service. Technologies like natural language processing and sentiment analysis can help companies better understand how to respond to customer feedback and questions. At the 2017 Google Cloud Next conference in San Francisco, Apoorv Saxena, a product manager on the Google Cloud team, hosted a breakout session explaining how organizations can use Google products to improve their customer service. He began by outlining the two different approaches that companies can take to machine learning. The first approach, Saxena said, is to use pre-trained models in the form of APIs to handle the machine learning needs of the company.

If IBM is looking for a new application for its Watson machine learning tools, it might consider putting health care providers' procurement and systems integration woes ahead of curing cancer. The fall-out from that project has now prompted the resignation of the cancer center's president, Ronald DePinho, the Wall Street Journal reported Thursday. The university recently published an internal audit report into the procurement processes that led it to hand almost $40 million to IBM and over $21 million to PwC for work on the project, almost all of it without board approval. It noted that the scope of its review was limited to contracting and procurement practices and compliance issues, and did not cover project management and system development activities. The audit "should not be interpreted as an opinion on the scientific basis or functional capabilities of the system in its current state," because a separate review of those aspects of the project is being conducted by an external consultant, it said. The Oncology Expert Advisor was intended to take in medical literature, treatment options, research data and patient records, using IBM's Watson machine learning algorithms to provide clinical advice to help oncologists in the community to provide the same level of care as doctors at the M.D. Anderson Cancer Center.

IBM has partnered marketing cloud specialist Salesforce to deliver a unified AI- powered solution, bringing together IBM Watson and Salesforce Einstein. Both AI platforms will be deployed using a new integration practice formed by Bluewolf, an IBM company. As part of the partnership, IBM will deploy Salesforce Service Cloud across the company to transform its global product support services and gain a single, unified view of every IBM customer. Bluewolf's new Solution Accelerators for AI integration will develop new industry-specific functions used by enterprise clients to fast-track adoption of cognitive applications seamlessly. It's been a few weeks since IBM CEO Ginni Rometty attended the World Economic Forum in Davos, Switzerland.