From CSR to ESG, most businesses today have good intentions to stand up to their environmental and social responsibilities. Nevertheless, in order for them to reduce its environmental impact, they need to first estimate the effect of their activities in quantitative means. Producing such estimates could be challenging, especially for large businesses involved in multiple chains of production and distribution. This can be resolved by the use of IOT ( Internet of Things) and smart sensors. IOT allows automation of accurate and reliable data collection, which could then be fed into data analytic algorithms that outputs analysis of the different sources externalities or pollutions. Businesses could gain insights from these analysis and take actions.

Daniel Fallmann is Founder and CEO of Mindbreeze, a leader in enterprise search, applied artificial intelligence and knowledge management. CEOs and line-of-business leaders are smart people. But they don't know what their enterprise knows. As a result, their organizations miss out on a multitude of valuable opportunities. Organizations possess a wealth of data. However, the data is all over the place, held in siloed systems and various formats.

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As the digital world continues to modernise, and new technologies are developed, the AI and Data Strategy book simplifies the complexities and introduces a structured way to update your strategy to include AI and Data capabilities The book defines the technologies and why they are important and this includes Automatic cars, drones, robots, blockchain, data science, machine learning and internet of things. Most of us are unsure what this all means and may think it's a bit technical and over our head. In the end we really just want to manage our information more securely and be able to access it anywhere anytime any place. The book makes the connection between what the technology is and how it can help us achieve your goals in accessing information. The AI and Data strategy book will get you started on the what, how, who and why to enable you to build and implement an AI and Data strategy.

Legendary cosmologist Stephen Hawking said it could spell the end of the human race. Transportation industry-disrupting industrialist Elon Musk is worried enough about it to found a billon-dollar nonprofit to keep it in check. However you feel about it, Artificial intelligence and machine learning are more than just hype. When many people hear the term "artificial intelligence" they envision an intelligent and self-aware, artificial lifeform. However, despite what some of our best minds have said about a possible future, this is still science fiction.

Companies and researchers unveiled potential use cases of machine learning and its benefits were discussed and debated at length. Nevertheless, as organisations were opened to the realm of possibilities capable with machine learning solutions, hesitation grew and few made the leap towards a data-driven journey. But as the necessity of machine learning becomes more evident, 2017 will see trepidation and hesitation replaced by yearning ambition. More than providing a competitive advantage, enterprises will come to see the technology as an essential part of their "survival kit" in an ever competitive market. The rise and growth of IoT throughout 2016 has provided fertile ground for organisations wanting to adopt machine learning solutions.

So if you're an executive who cares about growing your business, all this AI media coverage may prompt two nagging questions. First, is the business potential of AI real or not? The answer to the first question is that the business potential of AI is real. Today businesses can start to apply AI to change the economics of automating business processes requiring human intelligence. AI could allow you to increase the volume of work through a human intensive business process by 100X while reducing unit economics by 90%.