The resurgence of AI has industry leaders counting the days until quantum computers go mainstream. There's been considerable progress on the quantum computing front since I blogged last year about how The European Quantum Industry Consortium (QuIC) was developing its Quantum Strategic Industry Roadmap. For an update, I reached out to Laure Le Bars, research project director at SAP and also president of QuIC. Le Bars was a recent guest on the Future of ERP Podcast from SAP, hosted by Richard Howells, vice president for thought leadership at SAP, and Oyku Ilgar, marketing director for SAP Supply Chain. Advances in quantum hardware, middleware, and software will lead to a general-purpose quantum advantage machine being developed by 2030.

The most immediate benefit of artificial intelligence (AI) for business is increasingly clear: it's a huge opportunity for increased productivity. Gartner recently calculated that In 2021, AI augmentation will create €2.6 trillion of business value and save 6.2 billion man-hours globally and a survey by McKinsey has estimated that AI analytics could add around $13trn, or 16%, to annual global GDP by 2030. The easiest and fastest way to implement business AI is to add machine learning to existing business processes. Automation brings the most value when it's applied to narrow, repetitive business decisions that are made thousands of times a day, replacing the more boring aspects of knowledge work. For example, machine learning has proved successful at automating repetitive finance tasks such as the automatic matching of invoices and payments, increasing rates from 70% to 94% in just a few weeks--resulting in massive savings in time and effort.

Organizations are just starting to tap the incredible computational powers of AI for creativity, human productivity, and business results. If you thought judgment, ethics, and even creativity were the unique purview of humans, think again. The latest industry analyst predictions about artificial intelligence (AI) are out, and they're certain to oust a ton of assumptions we've made to date. Read on to find out just how smart, creative, and sincere AI will become during the next few years. Noting that South Africa granted the first patent to a creative AI system in 2021, Forrester researchers predicted creative AI systems will win dozens of patents in 2022.

If you thought judgment, ethics, and even creativity were the unique purview of humans, think again. The latest industry analyst predictions about artificial intelligence (AI) are out, and they're certain to oust a ton of assumptions we've made to date. Read on to find out just how smart, creative, and sincere AI will become during the next few years. Organizations are just starting to tap the incredible computational powers of AI for creativity, human productivity, and business results. Noting that South Africa granted the first patent to a creative AI system in 2021, Forrester researchers predicted creative AI systems will win dozens of patents in 2022.

As device sensors proliferate across every company's value chain – from new product development through inspection, tracking, and delivery – tinyML is surfacing to provide actionable insights, transforming business as we know it. There are sound economic reasons for all this interest and activity. McKinsey researchers predict IoT will have a potential economic impact of US $4-11 trillion by 2025, identifying manufacturing as the largest vertical (US $1.2-3.7 trillion). The rise of tinyML to collect data from edge devices at worksites anywhere was inevitable given the explosion of sensors in pretty much every industry across global supply chains. The tinyML community was established in 2019.

Artificial intelligence (AI) is shedding light on one of the most examined yet least understood experiences of modern life: the customer journey. From shopping malls and sports arenas, to train stations and city streets, C2RO is an AI-powered video analytics platform that captures anonymized data about people's movement so organizations can improve the customer experience. "We analyze human behaviour in physical spaces, and transfer it into actionable data," said Tim Heaney, vice president of sales at C2RO. "With a fact-based understanding of the amount of people coming into a space, how they move through it with whom, where they linger, and what they touch and eventually purchase, organizations can manage physical environments more efficiently to improve the customer experience and business results." A transportation organization used data from C2RO to improve subway train and bus terminal planning. "Based on the number of people boarding and leaving trains at certain times and days, as well as which direction they're headed at terminals, transportation managers could alleviate traffic crunches," said Heaney.

Intelligent chatbots are proving that there's no talent shortage when you know how to personalize employee recruitment. Just ask Bipul Vaibhav, founder and CEO of Skillate, a startup in India with an AI-based talent intelligence platform. In the post-pandemic job market, AI-based intelligence is just what recruiters need to attract top talent quickly. "We help organizations quickly find the most qualified candidates, using intelligence to speed up hiring while improving the candidate experience and addressing diversity and inclusion objectives," said Bipul Vaibhav, founder and CEO of Skillate. "Candidates appreciate having clarity on where they stand and what to expect next, reflecting well on the organization's culture, and improving its ability to attract top talent over time."

Explainable AI provides a whole new layer of insight by allowing analysts to clearly see why a prediction was made. When it comes to Enterprise AI (Artificial Intelligence), we often focus on automating repetitive business processes for a very simple reason and it doesn't take much imagination to see the value. But what if you wanted to gauge the impact of an unexpected event, such as a hurricane, on your business's bottom line? Maybe you'd like to compare the probable financial outcomes of a strategic decision before you make it? Explainable AI, which combines Human Intelligence with Artificial Intelligence, means employees now have the visibility to make these decisions.

Consumer fashion may be among the most unpredictable markets on the planet, but one startup in India has created an AI-based demand sensing platform that combines the brilliance of data scientists with seasoned industry experts to ferret out trends with uncanny accuracy. The idea is to close the gap between supply and demand. Omni-channel retailers are using AI to synch design and merchandising decisions with breaking consumer demand trends for sustainable growth. "We help companies create demand-driven fashion forecasts from consumer data across a holistic value chain," Ganesh Subramanian, founder and CEO at Stylumia. "Our demand sensing engine collects and analyzes publicly available global data to rank product trends, providing fashion designers, retail buyers, and merchandisers with a much deeper understanding of real-time consumer demand signals."

The ancient Silk Road, once the longest overland trade route, ran over 4,000 miles long. Today nestled in Eurasia's heart along the Silk Road is the national railway company – Kazakhsthan Temir Zholy (KTZ). Though traversing across this historic pathway sounds rather cool, the complex geography and harsh weather conditions propose serious challenges in operating cargo and passenger transportation. KTZ is a crucial part of Kazakhstan – the world's ninth-largest country – and its economy. This railway company knew the importance of having a seamless operating model in order to maintain its current operations, both on and off the track.