If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
How hot has Summer 2018 been around the globe? The speed of evolution in this industry segment is almost without precedent. Firms that had revenues worth tens of millions of U.S. dollars just a couple of years ago are talking about reaching a billion in revenue in just a couple of more years. But the reality is that it's the perfect storm – or heat wave – of innovation and capital intersecting at just the right time. Of course, it doesn't hurt that enterprises have already captured most of the potential value from offshore labor arbitrage.
Is artificial intelligence finally starting to take on a recognizable shape, after its history of being sometimes overhyped, often misunderstood, and always intriguing (but in a tantalizingly futuristic sort of way)? To better understand the state of AI development, the firm this year conducted deep interviews with executives at 30 of the world's largest companies, as well as three of largest providers of AI solutions and services. Out of this work, eight trends came into view. Rapid shift from experimental to applied technology. "Less than three years ago, many leaders in large organizations were asking themselves if AI could support their productivity and growth objectives, and many were just beginning to pilot and test AI applications," KPMG said.
Leaders need to rapidly realize the potential of artificial intelligence (AI) to accomplish their missions. Yet today, deployments rely on custom-built models and "one-off" integrations. Despite massive investments, organizations struggle to move AI from the lab to production at scale. Booz Allen is applying lessons learned from some of today's most complex AI engagements to replace costly, cumbersome deployments with open standards and plug-and-play interoperability. Discover – Access proven, pre-trained, explainable models.
Two years ago artificial intelligence (AI) reached the peak of absurd expectations, as I tried to capture in this post. Well, reality seems to have crept in, something that shows in how companies have been approaching AI, which has been to focus on low-hanging fruit, rather than moonshots. This is according to Deloitte's State of AI in the Enterprise, 2nd Edition, which unveils a world increasingly serious about AI. That said, there are still some head-scratchers in the data. Let's dive into the report.
Enterprises spanning virtually all industries and markets are jumping onto the artificial intelligence bandwagon. Yet as they climb on board for a ride into the future they soon discover that stock AI tools aren't capable of meeting their exact business needs. However, organizations don't need to spend large amounts of time and money building their own AI tools to fix this problem, suggested Kevin McMahon, executive director of mobile and emerging technologies at digital tech consultancy SPR. All they have to do, he noted in an interview, is to customize already existing tools to fit their exact business needs. To be effective, AI software must be tailored to address specific business problems, and this is where generic algorithms often fall short, said Sanjay Srivastava, chief digital officer at professional services firm Genpact.
We believe that automation and artificial intelligence (AI) will have a profound impact on our organisation which employs over 270,000 employees globally. Our people are highly educated professionals dealing with huge amounts of big data, therefore we want to ensure that we are in control of the disruptive forces of these technologies on our own terms. We also advise companies and governments who want to understand how this will impact them, so we have undertaken comprehensive analysis and research. We used our team of economists and analysts to model the susceptibility of jobs to be automated by the effects of tech such as AI. The headline figure suggests that up to 30% of existing jobs could become highly susceptible to automation by the mid-2030s, with some variability across industry sectors, by education, gender and geography.
Interest in artificial intelligence is on the rise in Egypt as enterprises embrace emerging technology to expand into new markets, investors back AI startups and government initiatives support education and awareness of the technology. There is mounting evidence that private enterprise is embracing AI. Recently, for example, AI and anlytics vendor fonYou partnered with a mobile operator in Egypt to use its AI module to reach the unbanked, and Widebot just raised a six-figure (USD) Pre-Series A investment for its Arabic language chatbot. Meanwhile, the government is looking to develop AI capabilities in a number of ways, including launching its first AI faculty at Kafr El Sheikh University. Egypt is aiming to have 7.7 percent of its GDP derived through AI by 2030, a figure touted in the PricewaterhouseCoopers (PwC) report, The Potential Impact of AI in the Middle East.
PwC announced that it was cited as a Leader in The Forrester Wave: AI Consultancies, Q3 2019. On firms that provide Artificial Intelligence (AI) consulting services, Forrester notes that "offering, breadth of support, and innovation are key differentiators." The report states that: "PwC doesn't see a technology problem; it sees a business problem. PwC's "reframing" approach for digital carries through to the firm's AI practice: PwC doesn't come to fix the plumbing but instead to transform a client. While many AI engagements address business process and customer experience, PwC doesn't stop there. The firm also illustrates how AI can change the way executives work by presenting interactive simulations of markets that they aren't in, they aren't optimised for, or don't exist. This allows leaders to imagine and execute on new business models and new products."
Robotic Process Automation (RPA) is the automation of repeatable and redundant, rule-based human action through the use of software bots. These software robots are installed on a user's machine or as a standalone self-managed automation, that can amimic a worker's actions and replicate these activities on their own. Once the bot has performed its designated tasks, they can then report, notify, or handoff to another bot. While RPA provides a breadth of opportunities for organizations to streamline mundane tasks and reallocate resources to focus on more complex endeavors, one of the biggest obstacles to adopting this technology is human nature itself. In any workplace, there are those who embrace change and those who reject it.