I'm sure we all remember the story of "The Little Engine That Could." A little railroad engine was built for pulling a few cars on and off the switches. When more powerful engines are asked to pull a load over a steep hill, they respond "I can't; that is too much a pull for me". So, the little engine asked to do the job. As the little engine bravely starts pulling the load, the engine starts puffing faster and faster chanting "I think I can, I think I can, I think I can."

I would love to learn more about your work as a government policy adviser on AI, infrastructure, education, and smart governance. Could you share about your role in crafting the National AI Roadmap under the Philippine Department of Trade and Industry? In what ways is this project important strategically for the Philippines? Many enterprises and organizations already consider data science and artificial intelligence (DSAI) as strategic capabilities. They are no longer optional, "nice-to-have" capabilities, but necessary, "must-have" -- a matter of organizational survival.

"The product was just never good," the noted venture capitalist said today in a wide-ranging fireside chat with Sisu CEO Peter Bailis during the Future Data Conference. There's no denying that Horowitz has had an outside influence on tech startups with Andreessen Horowitz, the Menlo Park, California investment firm that he co-founded with Marc Andreessen, the co-author of Mosaic and the founder of Netscape. The list of current investments and exits on the venture capital company's website is simply ridiculous. The storied Sandhill Road firm is currently invested in Sisu, which shows promise as a next-gen analytics system that uses machine learning to help people ask better questions of the data. Andressen Horowitz, which has $12 billion under management, has helped fund a variety of ecosystem tool players featured in these pages, like Alluxio, Anyscale, Cazena, Databricks, and Fivetran.

It has been widely tipped that 2020 is the year in which artificial intelligence is going to fully arrive in our workplace. But is it really the case? And how much is HR getting on board with this much touted digital revolution? According to a just-released report by Udemy for Business, 2020 workplace learning trends: The skills of the future: "AI brings with it a proliferation of data. Organisations and their employees will need to manage, store, process, analyse, and draw actionable insights from the data generated by AI. "Becoming a data-driven culture will be essential for organisations to harness the power of AI and big data." That said, it appears that most companies are not yet prepared factor in the impact of new technologies – with recent figures suggesting just 26% are ready. "With large-scale technology disruption, organisations will need to respond in a transformational way.

Fourteen years ago, one of us (Davenport) wrote an article about how companies were beginning to compete on analytics. In the years that followed, data and analytics seemed to become embedded in business culture. Whether these tools were called analytics, big data, or artificial intelligence, organizations of all sizes and types supposedly embraced these resources as a way to improve decision-making and enhance offerings. How to explain, then, a recent Deloitte survey of U.S. executives that found that only 10% of companies are competing on their analytical insights, and that the most popular tool for analyzing data -- used by 62% of companies responding to the survey -- is the spreadsheet? Our survey results clearly show that analytical competitors represent a minority of businesses today, despite the number of years technologies like big data and analytics have been readily available.

In my previous post, I suggested that it was possible to provide a road map that would help with the introduction of artificial intelligence, advanced analytics and machine learning into insurance companies. This post outlines the process. The first area to address is applications where the adoption of analytics will have an immediate impact on cost reduction and efficiency. The obvious point is process automation. In many insurance companies, the first projects involving advanced analytics and machine learning models are the digitisation and optimisation of processes.

For six consecutive years NewVantage Partners has conducted an annual survey on how executives in large corporations view data. This year, results show nearly every firm is investing in some form of analytics, and most are seeing value. But only one-third say they have succeeded in creating a data-driven culture. And many fear disruption by firms better equipped to use AI. Almost four in five respondents said they feared disruption or displacement from firms like those in the fintech sector or firms specializing in big data.

For six consecutive years NewVantage Partners has conducted an annual survey on how executives in large corporations view data. Each year the response rate increases, and the reported urgency of making effective use of data increases as well. This year the results are both more encouraging and more worrisome than in the past. Six years ago, the primary focus of questions and answers in the survey was big data, which was relatively new on the business scene. In the 2018 survey, the primary attention has moved to artificial intelligence.

We live in an increasingly data-driven society, in which information is becoming as much of a currency as money. Many consumers use free services from internet giants like Google, Facebook, Amazon, Microsoft and Apple, for example, and in return allow these corporations to track and monetise their online behaviour. One of the biggest questions of the day is the openness of such transactions, and the level of control that individuals have over the fate of the personal information they -- sometimes unwittingly -- divulge to organisations with which they interact online. Recent votes on both sides of the Atlantic have highlighted the capacity for data-savvy organisations to hoover up and profile large amounts of user data -- including demographics, consumer behaviour and internet activity -- in order to micro-target adverts, news stories and services in support of particular goals or causes. Clearly, the data floodgates are now opening for businesses of all sizes and descriptions, bringing myriad opportunities for timely analysis in pursuit of competitive advantage.

In the early 1990s, the general public made its earliest forays into using the Internet. At the time, no one could have imagined where the technology would lead. Social media, e-commerce, mobile apps, cloud computing, software as a service – the list is endless. Entire classes of applications – even industries – were not even a gleam in their creators' eyes. Today these internet-based technologies have transformed the way we live and work.