Artificial intelligence holds great potential for public-sector institutions around the world to improve government operations as well as service to citizens. But governments don't necessarily have experience in acquiring modern AI solutions and can tend to be cautious about harnessing new technology. By helping to guide the process of procuring AI, we aim to address major AI adoption pain points early in the process and make it easier for governments to implement this advanced technology. Overall, the guidelines aim to assist all parties involved in the procurement life cycle – policy officials, procurement officials and government commercial teams, data practitioners, and AI-solutions providers – in safeguarding public benefit and well-being.

This year "is the year that AI is going to enter the enterprise mainstream adoption," said Jeff Loucks, executive director of The Center for Technology, Media & Telecommunications at Deloitte Services LP. Deloitte's 2020 edition of its annual "State of AI in the Enterprise" report, released in July, indicates that many enterprises are investing heavily in AI, and many are buying cloud-based AI products instead of building their own. The technology and consulting company surveyed 2,737 IT and line-of-business executives across nine countries. All of the respondents use some form of AI in their companies. The survey showed that 53% of the adopters spent more than $20 million over the past year on AI-related technology and talent, with 71% of them expecting to increase spending in the next fiscal year.

You may not be entirely comfortable talking about automation as there are so many technical terms such as, for instance, «Artificial Intelligence» or «Robotic Process Automation». A lack of dedicated automation functions and roles in your organisation, and potentially significant workforce implications, can make automation as an initiative intimidating. These sentiments toward automation are common: You are not the only one facing a challenge in building sustainable, scalable automation projects. Business processes today are still designed for the days when large organisations had to rely on manual labour forces. It is especially important today that workforces focus on tasks that require social skills and creativity, instead of making them execute manual and repetitive rule-based processes.

Artificial intelligence (AI) is gradually being implemented in almost every aspect of our lives. In medicine, geology, customer data analysis, autonomous vehicles and even art, its applications are everywhere and its uses are constantly evolving. However, AI has raised at least as many questions as it has answered, including how the technology is defined and used (assisted vs. augmented vs. autonomous intelligence, for example), whether computers are capable of thinking in the same way as humans (the so-called Turing test), the broader impact of automation on society, and the unanticipated ethical and moral dilemmas it may cause.

GlobalData research has found the top big data influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named ten of the most influential people in big data on Twitter during Q2 2020. Evan Kirstel is a B2B thought leader with extensive experience across enterprises sales, alliances, and business development. He currently serves as chief digital officer and advisor of NYDLA.ORG, a remote, distance/digital learning and collaboration association. Kirstel highlights the challenges of data ingestion within the healthcare context, and also stated that enterprises are collecting massive amounts of data but do not how to leverage it effectively.

Companies increasingly rely on artificial intelligence to automate crucial tasks. Machines with brains work alongside humans in warehouses, make recommendations about who should get credit, triage patients seeking care, and analyze dizzying quantities of financial data. Lately, corporate boards have begun to worry about the ethical ramifications of turning so much power over to the machines. A study of 2,737 executives released this month by consulting firm Deloitte found that a majority of those who used AI in their business reported "major" or "extreme" concerns about ethical risks. "Even 18 months ago, ethics was not as much a part of the conversation as it is today," said Beena Ammanath, who leads the AI Institute at Deloitte.

AI solutions are proliferating, from custom offerings to enterprise applications to devices with embedded capabilities. However, this year's Deloitte AI survey found a growing awareness of the associated risks and wide variation in companies' preparedness for mitigating them. Over the past few years, more and more companies have been experimenting with AI, advancing their data-related capabilities, acquiring new technologies and talent, and integrating AI into their business processes. In coming years, AI will likely become even more pervasive. Just as companies no longer talk about isolated mobile strategies--they're just part of doing business--AI will soon become standard and routine, maybe even sooner than expected.

In the age of digital transformation, an increasing number of organizations are looking to tap artificial intelligence (AI) technologies to streamline day-to-day operations and revolutionize their business models. Last week, the consulting firm, Deloitte, released its third annual "State of AI in the Enterprise." The report gives a detailed look at the ways in which organizations are utilizing AI and provides insights into concerns shaping enterprise adoption moving forward. The Deloitte survey offers a detailed overview of AI adoption across the integration spectrum. To better understand attitudes alongside adoption, enterprises are divided into three smaller subsects--seasoned adopters, skilled adopters, and starters.

Now is a particularly opportune time to drive towards this goal. As the world moves towards a COVID-19 post-pandemic recovery, the UN has called on governments to heed the "unprecedented wake-up call" and "build back better" by creating more sustainable, resilient and inclusive societies. There are two approaches to Green AI – using AI to solve sustainability challenges and using AI in a more sustainable way. How can AI solve sustainability challenges? Delivering societal and environmental well-being through AI are key strategic considerations of the European Commission, who acknowledge that "AI systems promise to help [tackle] the most pressing concerns, including climate change and environmental degradation".

New Delhi: Global professional services company Accenture on Saturday announced to elevate Sanjeev Vohra as global lead of its Applied Intelligence business that helps customers use data, Artificial Intelligence (AI), analytics and automation to fuel business transformation. Vohra who is currently Accenture's growth and strategy lead for technology, would also join the company's Global Management Committee (GMC), it said in a statement. "We will count on his exceptional business acumen, leadership, and innovation-led mindset to drive our Applied Intelligence business and help our clients discover new ways to harness the power of data and insight to fuel their transformation and growth," said Annette Rippert, Group Chief Executive, Accenture Strategy & Consulting. Vohra who joined Accenture in 2002 would oversee a global Applied Intelligence workforce of 40,000, with deep industry expertise and skills in areas including AI, data science, deep learning, machine learning and data engineering. Applied Intelligence is Accenture's approach to scaling AI-powered data, analytics and automation capabilities for clients.