The big tech giants are all-in on AI. Instead of charging 20 per user for Gemini in Workspace, Google is just including it from now on. "We believe that AI is not just another tool; it's a foundational shift in how work gets done," says Google's President of Cloud Applications in a blog post. What a shock, the guy selling melons thinks everyone should be buying melons. "…By removing the need to pay for an add-on to access our latest generative AI capabilities, we're simplifying our plans and pricing to bring the added value of Google AI to all Workspace customers."

Companies like C3.ai and Palantir have shown that selling AI technology can be quite lucrative. After all, these companies command significant market caps and are growing quickly. Yet selling AI technology remains difficult. Customers often want customized solutions that are based on their unique data sets. There are also the issues of adoption.

While SAP is a front runner among global companies addressing the ethics around artificial intelligence (AI), there is still plenty to learn. In September 2018, SAP released guidelines for the ethical use of AI, which declare, for instance, that AI built by SAP shall be human centered, guarantee transparency, and keep data secure. While SAP was the first company in Europe to put such initiatives in place, many other large enterprises, including Microsoft and IBM, have taken similar steps toward ethical AI. With no globally recognized norms or policies in place yet, SAP has emerged as a leading voice in the global conversation. Noga explains the mandate he sees for SAP: "Not only should our own AI be subject to ethical requirements, but we also want to help our customers to build and use AI ethically. Moreover, we aim to contribute our expertise to the discussions taking place at a global level."

YC-backed startup Proven wants to make it suck less for women to find skincare that works for them. The co-founders are taking what they describe as a "rational, logic-based" approach to figuring out which ingredients might be most appropriate for each individual. As a TC Disrupt battlefield founder once memorably put it during her on-stage pitch, the beauty industry makes a whole lot of money from a whole lot of BS. And skincare falls squarely into the'full of it' category, with its expensively marketed pseudoscientific claims touting'miracle' fixes that most definitely aren't. Proven's co-founders, Ming Zhao and Amy Yuan, say frustration when battling with this BS via their own skincare issues ultimately led them to found the business together.

YC-backed startup Proven wants to make it suck less for women to find skincare that works for them. The co-founders are taking what they describe as a "rational, logic-based" approach to figuring out which ingredients might be most appropriate for each individual. As a TC Disrupt battlefield founder once memorably put it during her on-stage pitch, the beauty industry makes a whole lot of money from a whole lot of BS. And skincare falls squarely into the'full of it' category, with its expensively marketed pseudoscientific claims touting'miracle' fixes that most definitely aren't. Proven's co-founders, Ming Zhao and Amy Yuan, say frustration when battling with this BS via their own skincare issues ultimately led them to found the business together.

Are you promoting AI to consumers, clients or colleagues? If you're in marketing today there is a good chance that you are. But how do you sell artificial intelligence effectively given all the hype and hysteria that surrounds the technology? Here are ten evidence-based recommendations for how to communicate AI effectively from a new Syzygy study that captured people's feelings towards AI across the US, UK, and Germany (n 6000). With all the hype and hysteria around AI, people are suspicious and skeptical.

In the media, in movies, and in pretty much every piece of marketing collateral tech companies produce these days. Fortunately, you're driven and self-motivated, so you've taken it upon yourself to get educated about what AI is and isn't and how it can help your company. You've sorted through the noise and done your research. You're familiar with Natural Language Processing (NLP) and examined how it differs from the keyword-based search technologies your company has been using for the last decade. You've read up on machine learning and semantic search concepts and have begun to understand how they factor into customer self-service efforts, deflection rates, and creative engagement tools like chatbots. And you're ready to bring your newfound knowledge and ideas for transforming your company's operations up the chain.