Such exercises are always interesting but also inherently risky – particularly in uncertain times such as those we have recently experienced and continue to live through. Learn about the leading tech trends the world will lean into over the next 12 months and how they will affect your life and your job. For example, few at the end of 2019 would have forecast that the world of work would be turned upside down during the following year by a global pandemic, leading to an unprecedented focus on devices and services that facilitated remote working, and ushering in a likely permanent shift to a hybrid model. Then, just as economies were adjusting to and recovering from the pandemic, Russia's invasion of Ukraine in February 2022 caused a sharp rise in energy prices, increased inflation, supply chain issues and fears of widespread recession. This series of shocks has profound implications for the IT industry that look set to continue through 2023 and beyond.

Multinational technology corporation IBM calculated that 72% of business leaders cited fraud as a growing concern in the last year, that $44 billion will be lost worldwide due to fraud by 2024, and that a quarter of e-commerce sales transactions that were declined by artificial intelligence (AI) were false positives. AI has become the leading tool for fighting fraud, but it can still be improved upon. In the past, rule-based engines and simple predictive models were used to computationally identify the majority of fraud attempts. But these methods have not kept up with the increasingly sophisticated nature of fraud attacks today. With a proliferation of digital technologies at criminals' disposal, fraud has grown in both scale and severity over the last few decades. Large criminal organizations and even state-sponsored groups use AI-like machine learning (ML) algorithms to defraud digital businesses for millions of dollars each year.

Data is a company's most powerful asset. Yet, many businesses cannibalize this valuable asset by selling it to third parties when they should be using it to make their businesses stronger and more sustainable. Nearly all digital businesses collect some type of data from their users, so there has been growing concern from privacy rights groups about how that data is used. Yet, data collection is not wrong in and of itself. It's the why, how and what is done with it that matters most when it comes to building a profitable and sustainable business that simultaneously respects the privacy of its users.

Forrester has released its predictions for digital business in 2021, and it sees big changes coming as the post-pandemic era continues to rapidly transform the business landscape. "What many considered optional became imperative overnight," Forrester said of digital business, citing that one retailer saw five years' worth of digital adoption happen in only five months due to COVID-19 lockdowns. Digital engagement will become the number one driver of customer value in 2021, Forrester predicts, and many global organizations will join organizations like BP, John Deere, and Siemens in launching data, artificial intelligence (AI), and software-driven divisions. "By the end of 2021, we expect 30% of $1 billion-plus firms to have a significant digital product portfolio and 20% to stand up digital divisions dedicated to launching disruptive products," Forrester said. "Every new digital division will embrace innovation through ecosystems, and we expect a further 50% of enterprises to make cloud-centric transformation a priority, moving business-critical operational apps and all experience apps into the cloud," Forrester predicts.

The term artificial intelligence conjures up all sorts of images at different levels of a workforce and across industries. Preparing to deploy an AI chatbot or a smart service, iRPA or other effort requires education and careful planning and promotion to overcome any resistance and boost understanding and support. Growth in the adoption of AI across every type of business is inevitable. However, acceptance will be uneven, even hostile, depending on the organisation and its traditions. Some companies are born with nothing but the latest technology, others are slowly transitioning from traditional working practices to that of a digital business.

In today's era of digital business, companies are intoxicated by the potential of technology-driven transformation. Retailers are wielding big data analytics to drive new customer experiences and increase sales while players in banking, insurance, and pretty much every other industry are making a beeline to machine learning (ML) and artificial intelligence (AI) to automate and reimagine key business processes. The possibilities are endless, and the future of digital business seems bright. Yet a persistent trouble spot remains the serious shortage of IT talent, particularly among candidates with proven expertise in coveted skills in areas like cloud, security and AI. The 2019 State of the CIO confirmed that finding and nurturing the right skills to support digital transformation and the ongoing IT agenda is a significant hurdle for many IT organizations.

Work has gone digital, paper is still important, but process intelligence sits at a higher level. Organizations in every vertical have always relied upon a certain quantity of paper since the dawn of known time and, despite the rise of digital, that basic truth isn't going to change. Although invoices are now largely digital, boarding passes live on smartphones and there's even an app (or two) for To-Do lists and notepads, a certain amount of paper will always feature as part of any firm's operational procedures. While the Western world replaces some of its paper consumption with technology, business growth in developing nations and the use of paper in packaging is thought to offset the trend for digitization. If we accept these basic propositions, then it should logically follow that the technology industry seeks to provide solutions to working with information in its digital form.

Those bemoaning the amount of spam in their email account's inbox (offers of suspiciously cheap Rolexes, notifications of windfalls, requests to help transfer funds from African states) may not be aware that spam exists for one reason: it works. In a similar way, because the profits from successful cybercrime are very healthy, specific individuals and organizations will always spend time and effort learning clever exploits and methods, because, on occasion, those methods work. Cybercrime is therefore here to stay, and because both end-users and cyber specialists are becoming better educated as to attackers' methods, the threat landscape will not only shift constantly but also become more complex, as methods used by bad actors will become more – although this is not intended as a compliment – intelligent. In general, companies of all sizes have deployed a combination of three cybersecurity measures. The first is a suite of pre-programmed (albeit occasionally updated) databases of known threats: their signatures, techniques, and modus operandi.

PerimeterX is a provider of scalable, behavior-based threat protection technology for the web, cloud, and mobile. By analyzing the behavior of humans, applications, and networks, PerimeterX catches in real-time automated attacks with unparalleled accuracy. Its security service PerimeterX Bot Defender accurately protects commerce, media, and enterprise websites from all types of automated or non-human attacks, at any scale. The company was listed in the Top 5 Cybersecurity Startups Of 2019 by Business Computing World and was ranked in the 100 most promising private artificial intelligence companies in the world by CBInsights. PerimeterX was founded in 2014 and is based in San Mateo, California and has raised $91.5M in total.

Rule-based engines and simple predictive models could identify the majority of fraud attempts in the past, yet they aren't keeping up with the scale and severity of fraud attempts today. Fraud attempts and breaches are more nuanced, with organized crime and state-sponsored groups using machine learning algorithms to find new ways to defraud digital businesses. Fraud-based attacks have a completely different pattern, sequence, and structure, which make them undetectable using rules-based logic and predictive models alone. What's needed to thwart fraud and stop the exfiltration of valuable transaction data are AI and machine learning platforms capable of combining supervised and unsupervised machine learning that can deliver a weighted score for any digital business' activity in less than a second. AI is a perfect match for the rapid escalation of nuanced, highly sophisticated fraud attempts.