In 2002, Amazon’s Jeff Bezos issued a memo that has entered tech industry canon. The memo, known as the “API Mandate”, is generally perceived as being a statement about technology at Amazon, and is therefore widely admired by technologists and wholly ignored by executives. This is unfortunate, because it’s no exaggeration to say that the API Mandate completely transformed Amazon as a business and laid the foundation for its success. Better still, unlike many things that global technology titans do, it is something that can be replicated and put to use by almost any business.

In this post, we’ll talk about the memo, and how it created the systems and incentives for radical organisational transformation. Read More

Companies capturing lasting value from artificial intelligence think differently, from the C-suite to the front line. Here’s how to make the shift from opportunistic efforts to a truly AI-enabled organization.

Executives have seen that the move from running artificial intelligence (AI) experiments and proofs of concept to capturing lasting value at scale requires an investment in strong foundations. These include aligning AI with core areas of the business; embracing important cultural and organizational shifts; and investing in new kinds of technology, training, and processes for building AI.

More and more organizations are adopting these basic practices, and those that do tend to report the highest bottom-line impact from AI. But successful organizations don’t just behave differently; our experience in thousands of client engagements around analytics and AI over the past five years shows that they also think differently about AI. At these companies, AI is etched in the collective mindset (“We are AI enabled”), rather than simply applied opportunistically (“Here’s a use case where AI can add value”). Read More

Most companies are struggling to realize artificial intelligence’s potential to completely transform the way they do business. The problem is, they typically apply AI in a long list of discrete uses, an approach that doesn’t produce consequential change. Yet trying to overhaul the whole organization with AI all at once is simply too complicated to be practical.

What’s the solution? Using AI to reimagine one entire core business process, journey, or function end to end, say three McKinsey consultants. That allows each AI effort to build off the previous one by, say, reusing data or enhancing capabilities for a common set of stakeholders. An airline, for example, focused on its cargo function, and a telecom provider on its process for managing customer value.

Scaling up AI involves four steps: (1) Identify an area where AI will make a big difference reasonably quickly and there are multiple interconnected activities and opportunities to share technology. (2) Staff the team with the right people and remove the obstacles to their success. (3) Reimagine business as usual, working back from a key goal and then exploring in detail how to achieve it. (4) Support new AI-based processes with organizational changes, such as interdisciplinary collaboration and agile mindsets. Read More

The Covid-19 pandemic was devastating for many industries, but it only accelerated the use of artificial intelligence across the U.S. economy. Amid the crisis, companies scrambled to create new services for remote workers and students, beef up online shopping and dining options, make customer call centers more efficient and speed development of important new drugs.

Even as applications of machine learning and perception platforms become commonplace, a thick layer of hype and fuzzy jargon clings to AI-enabled software.That makes it tough to identify the most compelling companies in the space—especially those finding new ways to use AI that create value by making humans more efficient, not redundant.

With this in mind, Forbes has partnered with venture firms Sequoia Capital and Meritech Capital to create our third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations. Read More

Where many companies tire of marginal gains from early AI efforts, the most successful recognize that the real breakthroughs in AI learning and scale come from persisting through the arduous phases.

Patience is a bitter plant, but its fruit is sweet. This Chinese proverb could well apply to the task of harvesting benefits from artificial intelligence (AI). Many organizations underestimate what it takes to sow true gains, be it selecting the right seeds, apportioning the right investment, or having a mindset willing to put up with the vagaries of the crop cycle. But for those that persevere, the rewards can be huge. McKinsey research finds that leading organizations that approach the AI journey in the right ways and stick with it through the tough patches generate three to four times higher returns from their investments.

These AI leaders get on a different performance trajectory from the outset because they understand that AI is about mastering the long haul. They prepare for that journey by anticipating the types of things that will make it easier to navigate the ups and downs, such as feedback loops that allow data quality and user adoption to compound and AI investments to become self-boosting. Where some companies tire of marginal gains from weeks of effort, leaders recognize that the real breakthroughs in AI learning and scale come from working through those small steps.

But only a small number of businesses have figured out how to make AI work in these ways. Read More

Non-compliant companies could face a fine of up to €20 million or 4 percent of turnover.

The European Union wants to avoid the worst of what artificial intelligence can do — think creepy facial recognition tech and many, many Black Mirror episodes — while still trying to boost its potential for the economy in general.

According to a draft of its upcoming rules, obtained by POLITICO, the European Commission would ban certain uses of “high-risk” artificial intelligence systems altogether, and limit others from entering the bloc if they don’t meet its standards. Companies that don’t comply could be fined up to €20 million or 4 percent of their turnover. The Commission will unveil its final regulation on April 21. Read More

Moore’s Law is dead, right? Think again.

Although the historical annual improvement of about 40% in central processing unit performance is slowing, the combination of CPUs packaged with alternative processors is improving at a rate of more than 100% per annum. These unprecedented and massive improvements in processing power combined with data and artificial intelligence will completely change the way we think about designing hardware, writing software and applying technology to businesses.

Every industry will be disrupted. You hear that all the time. Well, it’s absolutely true and we’re going to explain why and what it all means.

In this Breaking Analysis, we’re going to unveil some data that suggests we’re entering a new era of innovation where inexpensive processing capabilities will power an explosion of machine intelligence applications. We’ll also tell you what new bottlenecks will emerge and what this means for system architectures and industry transformations in the coming decade. Read More

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