As artificial intelligence and its capabilities continue to expand, AI may be able to broaden creativity for companies moving forward. Forrester found in a recent study that AI tools available to technology executives will assist with overcoming digital repetition and that AI can help empower more unconventional thinking. In addition, AI can help power a cooperative mindset for a team and make for better collaboration. "This is less about the technology and more about the way the use of the technology facilitates collaboration by breaking silos and enabling different roles to work together on a common goal," said Diego Lo Giudice, Forrester's vice president and principal analyst. "Like with agile, identifying AI opportunities and building AI solutions requires various disparate stakeholders and roles like data scientists, business domain experts, designers, developers and testers to sit around the table, brainstorm and let the creative ideas flow. In breaking the traditional siloed enterprise structures, the various stakeholders and roles are forced to work together on common objectives."

AI is finding its way into software of all kinds, from the voice assistants in your home to the algorithms in life-saving healthcare applications. But the broader AI use becomes, the higher the risk of "AI gone wrong" -- unintended decisions made by an algorithm. In this episode of What It Means, Vice President and Principal Analyst Diego Lo Giudice discusses the expansion of AI and the increased need for checks and balances. But testing AI is not as simple as testing traditional software. As Lo Giudice puts it, how do you test something when you don't know the desired or anticipated outcome?

The benefits of artificial intelligence are flourishing across several industries and finding its way to all kinds of technical aspects. From education to manufacturing the technology has served every sector for better while introducing various innovations across its verticals. But, as experts fear, the broader AI use becomes, the higher the risk of "AI gone wrong" which means the algorithms can evolve on their own to make unintended decisions. In a recent blog for Forrester, Vice President and Principal Analyst Diego Lo Giudice discussed the expansion of artificial intelligence and the increased need for checks and balances. However, testing AI is not as simple as testing traditional software and as Lo Giudice puts it, how can one test something when they don't know the desired or anticipated outcome.

A world where robots do all the testing seems a long way off. For starters, demand isn't there, said Diego Lo Giudice, an analyst and vice president at Forrester Research. Lots of platform makers are adding AI to software testing, but Lo Giudice isn't getting many calls from clients about this. From what he sees, Sypolt's experience is typical. "Once they try it, they like it and are interested in it," he said.

It has long been a dream of many CFOs to have within arm's reach a crack team of financial analysts who can provide rich insights on trends and possibilities hiding deep in data. Well, the unimaginable might finally be imaginable. Artificial intelligence -- or, at this moment, the foundational layers of AI -- holds the promise of extracting the kind of valuable financial information that will set companies free to confidently take chances and explore new opportunities. That promise has been foreseen by tech industry analysts and executives who believe that, while the first chapters of AI for finance are just now being written, it's nonetheless the right time to start looking at a technology that could revolutionize finance. "The ability of machines to crunch numbers is phenomenal," said Leon Katsnelson, director and CTO of analytic platform emerging technologies at IBM. "But they still try to emulate a gut feel, and it's not really a gut feel. In a way, cognitive learning is a way to build up gut feel. And you don't have to be a math scientist wearing a white lab coat to use this technology."

Part of the promise of artificial intelligence is that it will impact how software is developed. Disruptive technologies have become commonplace in the software industry, and lately, artificial intelligence (AI) is on many companies' radars. The month of November 2016 alone saw much activity in the AI space, including Amazon launching an AI platform; General Electric acquiring two AI startups to help it try and compete with IBM's Watson; Google launching an AI group for its cloud, and an AI startup backed by entrepreneur Elon Musk signing a cloud agreement with Microsoft. All of this comes on the heels of a report released earlier last fall by the Obama administration's National Science and Technology Council's Committee on Technology examining potential use cases of AI. The study, "Preparing For the Future of Artificial Intelligence," observes that AI-related technologies already "have opened up new markets and new opportunities for progress in critical areas such as health, education, energy, and the environment."

Everyone's talking about how AI will revolutionize so many things. Most of today's discussions take place at the application level, although AI will impact software development too. Some vendors, ISVs and consultants anticipate such a shift, but they aren't able articulate the specifics yet. For years, organizations have been building software using certain types of knowledge. Now, they also have to consider the probable impacts of AI.

Historian Francis Fukuyama in 1992 reckoned with the fall of the Iron Curtain and the replacement of Communist systems behind it with liberal democracies, we had reached the end of history. Can we say the same about software development? Has the arrival of the age of Agile meant that we can now talk about a similar full-stop? Is this the final word in software development? And if it's not, what's going to come after it?