Improved business cases, skills shortages and a dark side -- AI predictions for 2020

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Artificial intelligence is making its way into more and more areas of our lives. But what can we expect to see happen in this area in 2020? Some industry experts share their views on the latest AI trends.

Synthetic data specialist ARM Insight believes, "There will be a huge investment return gap between those using basic analytics or simplistic machine learning on data from those that are using true artificial intelligence. Machine learning simply won’t cut it any more. Artificial intelligence will be the only path to maximum data value."


Henrik Nilsson, vice president EMEA at Apptio believes adoption of the technology will need to be better aligned to business goals, "The adoption of AI and IoT is on the rise, as many organizations increasingly realize the business benefits of the technologies. However, as these technologies move into the mainstream, companies will struggle to quantify their value over time as their IT finance systems aren’t set up for this. In 2020, the ability to calculate long-term ROI from technologies whose costs aren't fixed will be increasingly important for CIOs and CTOs looking to justify their technology investments.

"IoT, for instance, will widen the cost base for the IT team as smart devices proliferate. While this may reduce other costs, such as labor, over time smart devices are likely to become another layer of legacy technology. This makes it hard to assess the total cost of ownership without having dedicated tools for doing so. Similarly, AI will produce fast results in the short term, cutting down laborious manual processes, but its value is harder to quantify over time. For both of these technologies, as with other emerging innovations, CIOs and CTOs will need to have a defensible strategy for proving their value in order to align with the needs of the business while balancing their budgets."

This is echoed by Richard Langham, EMEA managing director at Highspot, "In the year ahead, marketing and sales teams will continue prioritizing AI and machine learning more than any other department in enterprises today. But the digital age’s wealth of data has created two extremes. At one end of the spectrum, so far many teams have overanalysed the minutiae, letting predictive analytics alone guide their direction and losing their way in the process. On the other end, teams have shied away from the data deluge and continued to make choices based entirely on instinct and gut feelings, ignoring market signals."

Langham adds, "Next year, AI capabilities like semantic search and intelligent content recommendations will boost sellers' productivity and effectiveness -- with no signs of slowing down. While AI is more powerful than ever, the key to unlocking its potential is still firmly in our hands."

AI is also expected to begin making an impact via 'smart contracts' though Colin Earl, CEO of Agiloft believes progress will be slow, "While the promise of smart contracts were thoroughly hyped in 2019, their potential still won't be fully realized in 2020. Eventually, smart contracts will become a core component of contract management solutions over time but that transition will not happen in the next year. Artificial intelligence (AI), however, will make a measurable impact on contract management in 2020 as a critical driver for autonomous contracting. For example, by analyzing the metadata in counterparty contracts received, AI can pull out the clauses and highlight new changes and how they relate back to the clauses that the organization likes to use. AI will empower companies to easily make comparisons and drive negotiations, expediting the process and removing a manual layer."

The handling of AI workloads will present a challenge according to Cloudian CMO, Jon Toor, "As data volumes continue to explode, one of the key challenges is how to get the full strategic value of this data. In 2020, we will see a growing number of organizations capitalizing on object storage to create structured/tagged data from unstructured data, allowing metadata to be used to make sense of the tsunami of data generated by AI and ML workloads" He adds, “Object storage will be instrumental in helping to process AI and ML workloads in 2020 as this newer storage architecture leverages metadata in ways traditional file storage doesn't."

There's also the continuing issue of getting enough skilled people, John LaRocca, managing director, Europe/NA operations at Fractal Analytics says, "The demand for AI solutions will continue to outpace the availability of AI talent, and businesses will adapt by enabling more applications to be developed by non-AI professionals, resulting in the socialization of the process. Non-AI practitioners, such as knowledge workers and analysts, who are not skilled AI practitioners (but have great domain expertise), will start to develop rudimentary applications aided by automated AI engines. The onus will be on corporate training programs to retrain/upskill these new practitioners and on IT to enable them with automated AI environments that use AI itself (e.g., machine learning apps to help develops train models without having to write code). This is not unlike the historical lifecycle of analytics, and it will similarly benefit everyone in the ecosystem - businesses will expand their capacity to develop and benefit from AI apps, AI experts will be working on truly leading-edge applications and tie newly upskilled non-AI practitioners who will contribute more and have more marketable skills."

We're likely to see more of the dark side of AI too. Nilesh Dherange, CTO of Gurucul says, "2020 will see an increase in cyberattacks that use Artificial Intelligence (AI) / Machine Learning. Weaponized AI will be used by attackers to find and exploit weaknesses, and to take information gleaned from successful hacks to develop even more powerful attacks." He adds, "As machine learning development tools become simpler to use, criminals will be able to more easily leverage them in new attacks. While some AI attacks will be rudimentary in nature, they will grow more sophisticated with malware capable of adapting to obstacles. Techniques like AI-enabled spear phishing will let attackers launch phishing attacks at scale, increasing their chance for success."

Ben Goodman, CISSP and SVP of global and corporate development at ForgeRock belives AI created deepfakes will become an issue, "The heinous use of AI to create convincing deepfake videos is becoming more publicly known, and they represent a massive threat with potential to spread misinformation and slander individuals on a grand scale. The industry will respond to this threat by fighting fire with fire, and using AI ethically to discern whether a video is a deepfake or legitimate."

But AI will have a role in preventing fraud too says Labhesh Patel, CTO and chief scientist at Jumio, "Customer experience and fraud detection will go hand in hand in the finance industry, especially as Millennials are 2.5 times more likely than Baby Boomers and 1.5 times more likely than Gen Xers to switch banks. Machine Learning and AI will serve a dual function in financial services and banking. Not only will AI help speed up and improve the verification and accuracy of new customer onboarding, it will also provide a reliable means of continued identity authentication for each subsequent customer login in order to thwart sophisticated attacks. AI can quickly scan, analyze and confirm an individual’s online identify in a matter of seconds by simply capturing a selfie of the customer, comparing it to the initial onboarding photo of a government-issued ID document (e.g., driver's license or passport) and then running it through an algorithm to detect any suspicious activity or digital tampering (Photoshop fakes). Because this process is historically faster than relying on human detection, fiserves implementing an AI-based digital identity verification solution in 2020 will experience a dramatic improvement in fraud prevention while also maintaining high customer conversation rates through a more frictionless, repeatable customer experience."

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