Daniel Connell oversees the Market Structure and Technology practice at Greenwich Associates. Prior to Greenwich Associates, he was the CEO at Correlix, Inc., a leading provider of real-time performance optimization technology. Formerly, Dan was the Executive Managing Director at Standard & Poor's, and CEO of ComStock, Inc. He also served as the COO of Xinhua Finance Ltd., China's premier financial information, and Media Company. He has also been an executive-in-residence in the private equity industry and as a Board Member and strategy consultant to technology-focused content companies.
As we progress further into Industry 4.0, finance needs to further leverage new technologies to add real value to a business's bottom-line, yet it remains in its infancy stages. Industry 4.0 has impacted a range of industries, and with the digitisation of industrial value chains, many forget about finance, which has only touched the tip of the iceberg when it comes to leveraging new technologies. Disruptive technologies such automation, artificial intelligence (AI), the Internet of Things (IoT), Bots, blockchain and machine learning are thrusting the global economy into a new digital era. Instead of seeing all these new developments in isolation, finance must focus rather on connection points, finding ways to optimise them to provide greater value to the organisation. Companies risk losing ground if they do not understand the changes and opportunities Industry 4.0 brings.
Making data quickly actionable creates difficult challenges for the old data management order. Three new reports from Gartner bring into sharp focus the increasing urgency for enterprises of building value-generating operational applications infused with AI and ML – or risk falling forever behind. Urgency Builder #1: In its latest AI business value forecast, Gartner says that AI augmentation will create $2.9 trillion of business value in 2021. Urgency Builder #2: Gartner's AI and ML Development Strategy study finds that leading organizations expect to massively increase their AI/ML projects – from a mean of four this year to 35 by 2022. Urgency Builder #3: In its "Predicts 2019: Data & Analytics Strategy" report, Gartner says, "Effective data management is more critical than ever. While some companies have taken control of their data and turned it into a weapon for securing market dominance, many others are struggling with an issue that is putting the brakes on intelligence coordination: silos."
Arthur C. Clarke's famous comment, "Any sufficiently advanced technology is indistinguishable from magic," seems especially apt today, with cars driving themselves and phones starting to do real-time language translation. But the real super-power behind our smartphones, apps, servers, automated homes and autonomous vehicles isn't magic – it's silicon, in the form of advanced processor and memory chips. A vivid reminder of this was provided by Samsung Semiconductor, a world leader in advanced semiconductor technology, at its Samsung Tech Day on Oct. 23 in San Jose. The annual event is part of Samsung's ongoing effort to foster innovation across the technology ecosystem, with hundreds of attendees learning about and discussing the future of consumer and business technology sectors. Chip-stacking is a perfect example of how behind-the-scenes innovation creates new possibilities, like the 12GB LPDDR4X uMCP (UFS-based multichip package).
The organisation of tomorrow will be built around data using emerging technologies. Big data analytics empowers consumers and employees. This will result in real-time decision making and a better understanding of the changing environment. Blockchain enables peer-to-peer collaboration and trustless interactions governed by cryptography and smart contracts. Meanwhile, artificial intelligence allows for new and different levels of intensity and involvement among human and artificial actors.
Artificial intelligence is arguably the most disruptive technology to emerge over the last few decades. Consumers are producing data at record levels. It's estimated we'll produce 463 exabytes per day by 2025. Yet humans aren't equipped to process that complex information. We're starting to rely more on AI to interpret massive amounts of consumer and third-party data in real time, and to make it relevant for our uses.
Today, businesses rely heavily on data for insight. At the same time, there are many data-driven models and solutions available for businesses to choose from to get their insight. Be it for understanding customer behaviour or getting real-time information from the ground, data-driven models require the right tools to ensure efficiency. With artificial intelligence being an enabler for automation to get faster results, businesses need a solid foundation in their business model. AI business models can be used on almost any type of business today.
In MEAP, you read a book chapter-by-chapter while it's being written and get the final book as soon as it's finished. Save big on Manning books and liveVideo courses with our exclusive bundles! Each bundle is carefully curated to enhance your skills in a key subject area. Deep learning is exploding, driving everything from autonomous vehicles to real-time computer vision and speech recognition. New languages and new approaches to programming are always emerging.
Nikolas Kairinos, CEO and co-founder of Prospex and Fountech, explains why artificial intelligence is set to radically transform sales and marketing, and what businesses need to know to take full advantage of this technology. AI as a marketing tool to help businesses deliver a better customer experience was once considered an advantage reserved only for large and resource-rich organisations. But the widespread proliferation of AI technologies means that companies large and small can leverage its potential to generate powerful sales and marketing (SaM) initiatives. Excitingly, this can cost significantly less than traditional big-ticket campaigns. Businesses are clearly waking up to the potential of AI; two-fifths (40%) of marketing and sales teams already recognise the importance of this technology, in particular machine learning (a subset of AI) in ensuring they are able to pursue and accomplish their growth targets.
Artificial intelligence feels different from previous technologies as it forces us to explore the very boundaries between machines and humans. Will AI lead to whole new jobs and industries and a higher standard of living? Or are we facing a dystopian future, as smart machines increasingly encroach on activities and cognitive capabilities that not long ago were viewed as the exclusive domain of humans? A new book, "Human Machine: Reimagining Work in the Age of AI" by Accenture executives Paul Daugherty and Jim Wilson, looks at artificial intelligence's potential to transform the workplace, citing examples from the leading edge and drawing parallels between today's human-machine collaborations and how businesses in the past adopted--and were in turn transformed by--earlier technologies. There's some good news: The "Age of AI" will not come at the expense of human workers as some fear.