To compete, sales agents need a deep understanding of their customers -- staffing changes, corporate strategy, conference schedules, where their competitors are selling and more -- meaning there are thousands of pages on company websites to read, each containing potentially useful clues; tweets from company executives and industry publications to scan; and executive speeches and press releases to monitor. Who has time to cross reference a customer's retail inventory against all of Intel's existing product lines? Who can keep track of it all? A sophisticated advanced analytics program, SalesAssist uses artificial intelligence and machine learning to study publicly available customer data and proprietary sales records. Then it goes beyond summaries and trends, arriving at key -- and most importantly, actionable -- insights about customer goals and needs that Intel's salespeople can use to close deals.

If you want to successfully adopt and scale artificial intelligence (AI) in your business, a majority of C-suite technology leaders polled by IBM and Forbes Insights say this should be your strategy: Go big, or go home. Paradoxically, however, these surveyed executives from more than 200 global companies report that their organizations have yet to go big. For example, most are still experimenting with small-scale pilot programs, which are no guarantee of success. Why are greater ambitions with AI so challenging? We've culled a series of charts from the two surveys--which includes CIOs, CTOs, chief data officers and chief digital officers--that explore that paradox and show some of the challenges in AI execution as well as how companies are spreading their bets.

Achieving business results from artificial intelligence (AI) comes with a significant learning curve for any organization. It requires investments in data infrastructure and human talent; it also demands new organizational structures and cultural change. But the potential payoffs are transformative: 63% of companies that have adopted AI say it has boosted revenue in areas where it is used. How far along is your organization on the AI learning curve? Answer a few questions below--culled from a recent IBM and Forbes Insights survey of more than 200 technology leaders--and see how you stack up.

As businesses rush to adopt artificial intelligence (AI) for products and services--from driverless cars to algorithms that can spot cancer--technologists, philosophers and governments are starting to tap the brakes. How can we be sure that AI will be trustworthy? How can we know that its applications are unbiased, that they are secure from attack, protect privacy and will do more good than harm? To chart a path forward, the European Union has taken a leading role in laying out guidelines for how companies can put AI to work ethically and responsibly. Two years ago, the EU formed the High-Level Expert Group on AI--a group of 52 leaders from education, business, law and other disciplines--to develop a set of AI ethics guidelines.

Bashing Silicon Valley has become one of the few things both political parties agree on this election cycle. And they have good reason--the artificial intelligence (AI) and automation technology developed by the Valley's best and brightest minds is projected to displace the jobs of between one-quarter and one-third of American workers by 2030. The Brookings Institute estimates that 36 million Americans could have 70% of their work tasks replaced by automation. These alarming figures are attracting the attention of policymakers and politicians alike. Some are calling for a tax on robots. Others believe massive open online courses (MOOCs) are the answer to retraining millions of displaced workers.

Artificial Intelligence enables marketers to understand sales cycles better, correlating their strategies and spending to sales results. AI-driven insights are also helping to break down data silos so marketing and sales can collaborate more on deals. Marketing is more analytics and quant-driven than ever before with the best CMOs knowing which metrics and KPIs to track and why they fluctuate. The bottom line is that machine learning and AI are the technologies CMOs and their teams need to excel today. The best CMOs balance the quant-intensive nature of running marketing with qualitative factors that make a company's brand and customer experience unique.

Interview with Sri Ambati, CEO and Founder of H2O.ai The open source software movement produced iconic innovations like the Firefox web browser, Apache server software and the Linux operating system--the genesis of the Android OS that currently powers 86% of the world's smartphones. It also fostered a mindset around continuous improvement of tools that can be collaboratively shared, improved upon and distributed. Today, machine learning and artificial intelligence (AI) are beginning to enmesh themselves in the open source world. Can it have the same impact and influence?

The way we work is fast changing, and a lot of credit for it goes to artificial intelligence. Two years ago, Gartner reported that "7 per cent of top-performing companies rank AI/ML (artificial intelligence/machine learning) as a game-changing technology." But within a year, that figure swelled to 40 per cent. A Gartner report mentions that the augmentation of AI technology will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity in 2021. One of the critical aspects of AI is how it can be utilized to enable individual knowledge workers, boosting their productivity and feeding them timely information furthering key business objectives.

A new study shows that business leaders are taking steps to ensure responsible use of artificial intelligence (AI) within their organizations. Most AI adopters – which now account for 72 percent of organizations globally – conduct ethics training for their technologists (70 percent) and have ethics committees in place to review the use of AI (63 percent). AI leaders – organizations rating their deployment of AI "successful" or "highly successful" – also take the lead on responsible AI efforts: Almost all (92 percent) train their technologists in ethics compared to 48 percent of other AI adopters. The findings are based on a global survey among 305 business leaders, more than half of them chief information officers, chief technology offers, and chief analytics officers. The study, "AI Momentum, Maturity and Models for Success," was commissioned by SAS, Accenture Applied Intelligence and Intel, and conducted by Forbes Insights in July 2018.

A new study shows that business leaders are taking steps to ensure responsible use of artificial intelligence (AI) within their organizations. Most AI adopters – which now account for 72 percent of organizations globally – conduct ethics training for their technologists (70 percent) and have ethics committees in place to review the use of AI (63 percent). AI leaders – organizations rating their deployment of AI "successful" or "highly successful" – also take the lead on responsible AI efforts: Almost all (92 percent) train their technologists in ethics compared to 48 percent of other AI adopters. The findings are based on a global survey among 305 business leaders, more than half of them chief information officers, chief technology offers, and chief analytics officers. The study, "AI Momentum, Maturity and Models for Success," was commissioned by SAS, Accenture Applied Intelligence and Intel, and conducted by Forbes Insights in July 2018. AI now has a real impact on peoples' lives which highlights the importance of having a strong ethical framework surrounding its use, according to the report.