51 Artificial Intelligence (AI) Predictions for 2018

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It is somewhat safe to predict that AI will continue to be at the top of the hype cycle in 2018. But the following 51 predictions also envision it becoming more practical and useful, automating some jobs and augmenting many others, combining machine learning and big data for fresh insights, with chatbots proliferating in the enterprise.

As the automotive industry undergoes massive disruption, incumbent OEMs and Tier 1s are becoming increasingly aware that they need to adopt AI immediately to address not only the external vehicle environment but to understand the in-cabin experience as well. Semi-autonomous and fully autonomous vehicles will require an AI-based computer vision solution to ensure safe driving, seamless handoffs to a human driver, and an enriched travel experience based on the emotional, cognitive and wellness of the occupants—Dr. Rana el Kaliouby, CEO and co-founder, Affectiva

In 2018, I expect we’ll see a number of firsts, including AI systems which can explain themselves directly (‘first person’) instead of being externally assessed (‘third person’); the erosion of net neutrality due to increasingly personalized and optimized AI-driven content delivery; and the burst of the deep learning bubble. AI startups who have simply applied AI in a particular domain will no longer receive over-inflated valuations. Those that survive will be offering a fundamental and demonstrable step forward in AI capability. We’ll also see at least one more fatal accident involving autonomous vehicles on the roads, and a realization that human-level autonomous driving will require much longer to test and mature than current optimistic predictions—Monty Barlow, director of machine learning, Cambridge Consultants

AI will begin answering the question “Why?” Two things we’ve learned watching early adopters interact with AI systems over the last couple of years are: 1) Humans are not good at not knowing what an AI is doing, and 2) AI is not good at telling humans what it’s doing. This leaves users frustrated wondering “Why?” in the face of AI’s only current explanation: “Because I said so.” In 2018, it will no longer be enough for AI creators to shrug off users’ desire for more transparency by blaming the lack of communication on the fact that the machine is processing thousands of variables per second. In order to gain users’ trust that an AI system is working in pursuit of a shared goal, AI developers will begin prioritizing advanced forms of accountability, reporting and system queries that allow users to ask, “Why?”, in response to very specific actions—Or Shani, CEO, Albert

Personalized Dynamic Pricing. We predict a move of major ecommerce sites (mostly fashion, electronics, food and drugstore) to real time pricing personalization. Online and brick and mortar pricing will be based on behavior, supply and demand and competitive pricing. Unlike today’s dynamic pricing which changes according to variables specifically not customer-related, personalized pricing will reflect a unique offer received per shopper. Prices will change frequently to reflect a personal offer. The online experience will be emulated offline with all store supply tagged with electronic pricing. There will be a price on the page or on the shelf, and then there will be “your” price—the unique offer you receive—Dan Baruchi, CEO, Personali

In the near future, we’ll be looking at an AI vs. AI combat zone for the first time. Warfare, in general, will move from state actors, hackers and humans engaging in the process, to AI. AI will be directed to attack foreign states and corporations at a veracity that humans cannot defend, so now’s the time to discuss purpose-driven AI for good and regulations that should be put in place—Chad Steelberg, CEO and Chairman, Veritone

If you are a software company and are not thinking about adding some type of intelligent AI layer on your product or service, then you will be lagging behind others who will. AI is like water or the air around us — it’s not a category, but it’s everywhere and will be embedded in most software we use whether we know it or not—Ed Sim, founder, Boldstart Ventures

2018 is the year that AI becomes packaged and provided to the rest of us in ways that do not require a computer science degree. The goal isn’t to create The Singularity – it’s to make sound judgement scalable. Observe patterns. Learn from patterns. Apply and test guesses. Draw inferences. It’s brute force-based, but it happens so fast you and I don’t care – and it happens across a larger set of data than you and I could otherwise touch. But none of that matters if it isn’t provided to other software – and users – in a format that can be used and can yield results. We’re finally seeing APIs and client apps emerge that show we’ve hit that milestone—Mike Fitzmaurice, VP of Workflow Technology, Nintex

Silicon Valley won’t be the only place innovation in this area happens. Several countries around the world are placing big bets on AI. It will truly be the technological battleground of the future. If a company is going to commit to AI being a part of their future business plans, they better commit to a long-term development plan that might include several periods of rebuilding and disruption. AI is going to go through several periods of both slow and rapid change—Todd Thibodeaux, CEO and President, Computing Technology Industry Association (CompTIA)

AI is not about to leave the hype-cycle anytime soon. Current advanced analytics solutions will continue to transform into AI solutions using machine learning and deep learning. Looking to 2018, expect companies to invest in self-driving car research and implement features for assisted driving in new car models. An example of this is computer vision that enables a car to take control if the driver shows signs of fatigue. We predict that companies traditionally using statistical models for advanced analytics solutions – for example, to improve forecasting – will invest in machine learning based adaptive solutions, extracting data from internal and external sources to improve their models—Naresh Koka, VP, SPR

It’s now possible to blend AI with real-time transactional data flowing through a single platform. That opens a world of new possibilities. As an example, AI can help companies capitalize on perishable opportunities when data flows on a single platform, such as optimizing the cost per unit when sourcing a wide variety of commodities such as energy. On a platform with cost-per-unit information for energy from wind, solar and grid sources, AI can enable a company to adjust actions as costs fluctuate in real time, taking advantage of price changes to minimize energy expenses. That’s just one use case — AI and real-time transactional data can enable organizations to take advantage of other short-term opportunities as they arise—Bob Renner, CEO, Liaison Technologies

In 2018, AI technologies that are implemented in the enterprise will be human-centric and result in measurable business outcomes. These technologies will augment human intelligence to make us better versions of ourselves. AI that augments humans will be more widely accepted as it enhances skills and has a positive impact on society, as opposed to perpetuating fears of the human vs. machine—Joshua Feast, CEO and Co-Founder, Cogito Corp

We expect to see continued investments in AI by VCs and from technology and non-technology sectors. It’s the next step in our evolution to unleash and utilize full potential of data – whether sitting within an organization or connecting to external industry sources and macro-economic trends or data coming from sensors and devices. We expect insights from such data will be automated 70-80% of the time through training and learning. But it will require the right human skills and feedback loop aligned with technology advancements. Human expertise will continue to be required in this journey and we will see more focus shifted to strategic decision making—Subrata Chakrabarti, VP of Product Marketing and Strategy, Anaplan

In 2018, the implementation of “smart automation” will deliver the most immediate results to organizations. So many businesses still rely on decades-old, legacy-driven manual processes which create bottlenecks in the digital world of commerce. Automation technology has advanced to the point where these manual tasks—predominately in the back office and shared services centers—can be effectively taken out of human hands. Importantly, we’re now at a stage where business users themselves can manage this process, rather than needing full-time IT attention. This means we’re going to see CIOs have a say in more and more aspects of the business, as they build out enterprise-wide automation strategies. These strategies offer immediate value to companies, and will lay the foundation for long-term AI success—Dennis Walsh, President, Americas and APAC, Redwood Software

In 2018, we will see Artificial Intelligence (AI) technologies allow Business Intelligence (BI) to advance by many orders of magnitude—bringing about not just linear-paced sustainable innovation, but true exponentially disruptive innovation that we only see once every few decades. In today’s BI and Analytics space, it may take unnecessarily long—and millions of dollars—to query truly large complex data sets, measured in the many terabytes and petabytes of volume. With advancements in AI for BI, businesses in 2018 will be able to query very big data in milliseconds, enabling them to learn much more at much faster speeds, ushering in not only a transition toward greater Business Intelligence, but toward true business cognition—meaning that AI will finally be able to ‘understand’ business data in lieu of simply reporting on it—Guy Levy-Yurista, Head of Product, Sisense

When it comes to artificial intelligence in 2018, companies will begin to hire individuals who can properly analyze algorithms. We will call these people ‘algorithm whisperers.’ Next year, chatbots will be assisting everyone – from being incorporated into mobile phones, to the brick and mortar shopping experience. In the future, all products, services, and business processes will be self-improving—Timo Elliott, Innovation Evangelist, SAP

Advancements in analytics and AI will play a major role in healthcare this coming year. Not just within patient population tools, but also in optimizing workflows both within in-patient and out-patient scenarios. The age of EHR deployments are now pushing organizations to revise, enhance, and develop new processes within the care continuum. Essentially changing the way they work, treat patients, and receive care within the healthcare environment—Christian Boucher, Healthcare Evangelist,Citrix

AI will accelerate the extinction of simple order-taking sales. It will enhance consultative sellers’ ability to win more customers by effectively articulating business value. AI-powered sales learning tools will suggest actions, micro-training, and just-in-time content for reps—based on assessment of the customer’s needs, the rep’s skills and experience, and the competitive dynamic during sales, like the way Netflix recommends movies—Yuchun Lee, CEO and Co-founder, Allego

General purpose AI is still decades away. However, narrow AI applications will make a big splash in enterprise support functions in 2018, as call center, finance and IT executives begin to move conversational AI, image recognition and autonomic applications from pilot mode into production. These applications will complement existing robotic process automation implementations, turbo-charging employee productivity and operational speed to levels far beyond traditional industry benchmarks—Stanton Jones, Director and Principal Analyst, ISG

2018 will be the year that exposes where AI works and where it fails in healthcare. Applied to huge de-identified data sets, AI is already generating insights useful in population-based work such as accountable care and drug discovery. But AI fails badly when “resolving” to the individual care plan, mostly because the full set of data needed to treat a single human being is still too vast, complex, and mysterious for today’s computers and algorithms to “automate”—Frank Ingari, CEO, Growth Ally

I expect 2018 to be an even more exciting year for businesses on their journey towards the intelligent enterprise. More and more companies will grow out of proof of concepts and will effectively start to apply AI throughout the business. Thanks to mature machine learning algorithms, disruptive business models will emerge. They will force whole industries to realize that digital transformation is not just trend, but essential to remain competitive. Meanwhile, deep learning is established as the standard machine learning commodity, but will now strive for more efficiency and scalability within the systems. Finally, we can await further breakthroughs in reinforcement learning and will see academia further adjust to industrial research to ensure their competitiveness—Markus Noga, Head of Machine Learning, SAP

AI will drive up demand for data quality. Organizations are increasingly taking humans out-of-the-loop and empowering AIs to actually make decisions—about how to price flights, stock shelves, or even triage ER patients. At the same time, researchers are finding that “black-box” deep learning algorithms—which once trained can’t be tweaked or even really understood by humans—are the most effective for many problems. Since these algorithms are “garbage in, garbage out” and since the results of garbage-output are becoming ever more consequential, high quality training data will become a coveted resource, like oil for the information age. The sharpest human minds in tech may even shift their attention from creating algorithms to feeding those algorithms the best data diet—Aaron Kalb, co-founder and head of product, Alation

Advances in AI lead to specialized tools in the cloud. As companies look to innovate and improve with machine learning and artificial intelligence, more specialized tooling and infrastructure will be adopted in the cloud to support specific use cases, like solutions for merging multi-modal sensory inputs for human interaction with robots (think sound, touch, and vision) or solutions for merging satellite imagery with financial data to catapult algorithmic trading capabilities. We expect to see an explosion in cloud-based solutions that accelerate the current pace of data collection and further demonstrate the need for frictionless, on-demand compute and storage from managed cloud providers—Horia Margarit, principal data scientist, Qubole

This year, companies tapped AI and machine learning to transform the customer experience, making stories from sci-fi a reality by having robots in stores and using VR to let shoppers test-drive cars, design houses, and more. 2018 will be a time for these organizations to apply the lessons learned from working with AI in customer-facing capabilities to back-end processes by using the technologies to streamline and automate. They can also explore the power of coupling AI and machine learning with other tools, such as IoT, AR, and others, to further enhance front- and back-end functions—Moritz Zimmerman, CTO, SAP Hybris

In the same way that decades ago made it possible for any business to provide key information about the business 24 hours a day, we’ll see bots start making it possible for businesses to provide answers to the most common questions their customers have. Natural language processing and machine learning will be increasingly accessible to even small and medium organizations—Dharmesh Shah, co-founder and CTO, HubSpot

2018 will be the year of blended AI—even though interest in AI and chatbots is increasing, human interaction will never go away. While some brands have goals of decreasing their call volume by 50%, real-time interaction will increase (as evident by the Forrester prediction that more brands will phase out email in favor of real-time customer engagement communications). Human interaction will be at the epicenter driving AI in customer service, and is imperative for it to be successful and not see satisfaction levels drop. We still need cognitive thinking that can tweak the algorithms and step in to help customers when needed – brands shouldn’t leave everything to a bot—Dan Kiely, CEO, Voxpro

Data is the foundation of digital transformation initiatives and we are sure to see more major brands across both business and consumer industries leveraging AI-driven metadata in the coming year. This data about data, unified across the enterprise, will enable organizations to start realizing AI’s full potential. By applying machine learning and AI to metadata across the enterprise, businesses will be able to more quickly and accurately capture unprecedented insights and make intelligent predictions based on data – including things they never thought to consider. This will fuel innovation, create better customer experiences, enhance security of sensitive information, and improve overall business outcomes—Anil Chakravarthy, CEO, Informatica

In 2018, AI technologies that are implemented in the enterprise will be human-centric and result in measurable business outcomes. These technologies will augment human intelligence to make us better versions of ourselves. AI that augments humans will be more widely accepted as it enhances skills and has a positive impact on society, as opposed to perpetuating fears of the human vs. machine—Joshua Feast, CEO and Co-Founder, Cogito Corp

We expect that the AI market, specifically as it relates to chatbots, will continue to grow as advertisers gain a better understanding of how the technology can fit into their customer engagement plans and enhance the shopping experience. Chatbots empower brands to have direct, automated conversations with customers 24/7/365. The key for brands in 2018 will be to deliver relevant messages and engagement through this new medium (chatbots, or voice recognition devices) as part of a holistic consumer-centric approach that includes audience understanding, targeting, delivery and measurement—Pehr Luedtke, SVP of Business Development, Valassis Digital

Mobile ad tech is a data-driven industry and the perfect platform for AI and machine learning to thrive and make an impact. However, AI is yet to be adopted across the industry despite being able to solve pressing problems such as optimizing campaigns to reduce infrastructure costs, and dynamic creative optimization, amongst others. 2018 will bring synergies between AI and ad tech which will evolve with a wider adoption—Abhay Singal, co-founder and Chief Revenue Officer, InMobi

Making smart marketing decisions across all customer touchpoints, using all available data, to drive complex business outcomes is a herculean task—and artificial intelligence is an absolute requirement for making it all work. In 2018, we’ll finally start to see AI deliver on the omnichannel promise to make marketing that consumers—and others in the value chain—love. The technology is there—from players like IBM Watson and others—and now is the time to rally the right processes and people to put it in action—Dan Rosenberg, Chief Strategy Officer, MediaMath

AI will play an enhanced, proactive role in enabling exceptional customer experience in 2018, where fast and accurate resolution is key. Today, AI in the self-service space (e.g. chatbots) helps provide fast service for transactional or traditionally self-service resolved issues. 2018 will bring AI’s proactive, context-inclusive handoff of chat sessions to live agents, enabling quicker and more complete resolution of more complex customer needs—Chris Bauserman, VP Segment & Product Marketing, NICE inContact

AI will have a pivotal role in communication and collaboration. With new modes of communication attempting to stake a claim in the workforce, expect to see a significant change in the traditional work dynamic. Artificial intelligence, for example, is going to transform and customize the way people communicate with pattern and location recognition to streamline meetings and calls for each individual employee. Further, employees will shift from communicating through their devices to having their devices communicate for them—Mark Sher, vice president of product marketing for cloud voice, Intermedia

AI and data will take the gossip out of the real estate industry. Just as technology changed financial markets, we will see AI revolutionize the largest data asset class in the world, real estate. No more subjective opinions or guesswork; decisions will be based on AI working with massive data sets to create a truly competitive industry.  Regardless of whether we are talking about home price trends for a single block or an entire nation, AI will remove the constant gossip that attempts to inform the buying and selling decisions consumers, investors and mortgage lenders make—Jeremy Sicklick, CEO and Co-Founder, HouseCanary

Rather than being seen as a cure for everything, AI will get more practical in 2018. In fact, it will actually become less visible in many cases, as people focus more on the new ways that AI, when tightly integrated into everyday applications, solves specific business problems. Instead of just a concept, they will find that AI enables them to be more productive and able to discover new insights that they could not before. In addition, technology industry leaders and even AI customers will increasingly find it valuable to integrate disparate AI technologies—and discover that when integrated, these different AI technologies deliver more than the sum of their parts—Peter Wallqvist, VP of Strategy, iManage

In 2018, I expect AI techniques to be applied to solve more of the complex engineering problems organizations face in design, testing, and certification of engineering products. By utilizing knowledge management platforms to amplify and augment human decision making, AI can take historical data to make sense of problems that otherwise may not have been solved with traditional engineering—Mohit Joshi, president and head of banking, financial services and insurance, and health care and life sciences, Infosys

AI will become more accessible to non-experts. Early forms of business AI are demonstrating how they can help organizations scale and maximize efficiency, but before they reach mainstream adoption, they’re going to have to achieve mainstream usability. In 2018, we’ll begin seeing two trends: AI interfaces will become so accessible that non-technical users across organizations and roles will be able to operate them. Additionally, more and more developers will begin learning how to program AI systems, making AI less obscure and rarefied and more a part of the standard developer toolbox—Tomer Naveh, CTO, Albert

Data analysts begin to reap the benefits of AI. While “data analyst” seems like a job ripe for automation (isn’t that what computers do well?), the advancements in AI will lead to efficient assistants rather than replacements. We’re getting closer to a place where data analysts leverage AI for pattern matching and conducting closed environment analysis. Soon, the job of analysts will be to point the AI to the right questions to be analyzed and to decide how to interpret the results in the real world—David Crawford, director of software engineering at Alation

AI will help companies step out of the middleman role between offline and online. In 2018, online-first companies will be forced to make their way into the physical realm to connect with consumers. Technologies that enhance brands’ ability to connect once they’re offline—and integrate online audiences into the experience—will have significant impact. What currently stands in the way of many in-person experiences’ ability to extend online is companies’ need to control the associated social media content for brand “appropriateness.” AI will step in to take over by moderating and retargeting content in real-time, based on image analysis of image-based content, as well as its fit with predefined brand guidelines—Matthew Haber, Managing Director & Co-Founder, BeSide Digital

Enterprises will move from AI science experiments to truly operationalizing it. As enterprises move forward with operationalizing AI, they will look for products and tools to automate, manage and streamline the entire machine learning and deep learning life cycle. Data scientists need to focus on the code and algorithms and not automating and operationalizing the process. In 2018, investments in AI life cycle management will increase and technologies that house the data and supervise the process will mature—Nima Negahban, CTO and cofounder, Kinetica

The AI debate shifts from ‘is it good or evil’ to ‘is it ever going to be good enough’. If 2017 was the year where the warnings from Elon Musk and Stephen Hawking about the potential evil from AI clashed with predictions from Mark Zuckerberg and Bill Gates on its potential good, 2018 will be the year when the debate shifts to its practical utility. Much like other technologies that were lauded for their world-changing potential and then fizzled as the fog of the hype cleared, early adopters will find themselves disappointed by AI’s obvious limits. The broader public—familiar with Alexa, Siri and Google Home—will be similarly disillusioned as the experts acknowledge that there is only so much that AI will be able to do, and for really complex problems, a new paradigm will be needed—Michel Morvan, co-founder and CEO, Cosmo Tech USA

Developers will confront the question of open sourcing their AI/ML data sets. It is no secret that companies like Facebook, Google and Amazon currently have a monopoly on our data. In 2018, developers will need to make a decision: band together and open-source their AI/ML data sets in the hope of standing up to these monopolies, or give in and resign to a future where Mark Zuckerberg and Sundar Pichai remain the keeper of the keys to AI innovation. One technology that will make these developer-led, open-source initiatives possible is homomorphic encryption. Through homomorphic encryption, AI/ML models can be developed and verified on a blockchain before being shared, in turn liberating them from today’s limited and highly-centralized data sets. This approach paves the way to a more democratic and collaborative AI future while at the same time skirting any concerns with privacy and proprietary data—Matt Creager, Vice President of Growth and Developer Relations, Manifold

The rising AI tide lifts all technology boats, and, in cybersecurity, it means we can now make better predictions than ever before about never before seen threats. That, combined with great enhancements to automation, means that defenders may gain an upper hand on attackers. However, all technology, including AI, is dual-use, meaning it has the potential to be used for both good and bad purposes, depending on the intentions and actions of those who wield it. While the risk of the great robot uprising is somewhere between science-fiction and very far off, there are more immediate risks to AI, from the subversion of defensive AI by attackers, to AI-driven cyberweapons or campaigns. As defenders, our excitement about the benefits of AI are balanced with our preparations for such harmful exploitations—Joe Levy, CTO, Sopho

As AI-based cybersecurity technologies, including user behavior analytics, become mature enough for enterprise deployment, we predict that we’ll hear more success stories about how AI prevented a complex cybersecurity attack, with more companies allocating a direct budget for similar technologies in 2018 and beyond. We also think that vendors will extend their AI-related cyber security portfolio to support incident management. On the R&D side, we expect promising AI-based security announcements for securing IoT and smart cities—Csaba Krasznay, security evangelist, Balabit

In efforts to keep up with consumers’ desire for innovation, companies are rebuilding their legacy apps on the cloud. But, these rapid changes have given rise to complex IT ecosystems, which make it difficult to monitor digital performance and manage the user-experience effectively. That’s why, in 2018, organizations will look to AI to automate all the heavy lifting and proactively identify problems so that they can pinpoint the underlying root cause of any issues before their customers are impacted—Alois Reitbauer, chief technology strategist, Dynatrace

As enterprises ramp up their AI operations and build their own centers of excellence, we’re going to see a war for talent across a range of disciplines. Data scientists and cognitive programmers, linguists, psychologists, script writers and UX experts, are going to be in more demand than ever before—Chetan Dube, CEO, IPSoft

In 2018, AI will help companies scale and will take on a higher percentage of work. In 2018, business leaders will push to make the business run more efficiently and will turn to AI and machine learning for help. Companies will also turn to AI to help scale and do jobs instead of adding headcount. We will see AI developments and research move from the scientific/abstract concept phase to a more practical phase—Derek Choy, CIO, Rainforest QA

Artificial intelligence will dramatically change the accounting profession and recast the skillset required to succeed. We will see the rise of accountants as strategic advisors to small businesses as AI increasingly powers prescriptive financial decision making by sifting through vast amounts of financial data and empowering individuals to make recommendations about the best course of action. This will fundamentally alter the role of today’s accountant as focus shifts from tedious data entry, to using data-driven insights uncovered by machine learning to help small business clients make better business decisions—Herman Man, VP of product and partnerships, Xero

Alexa will start to use her eyes. With the release of the Echo Show and other forthcoming devices, Amazon’s extensive investment in vision-based product recognition efforts through its Lab 126 is coming to fruition. It follows that Alexa will start to use the camera to disambiguate between possible purchases, particularly for grocery. This will be important in on-boarding new shoppers where the machine learning algorithms don’t have the shoppers’ history modeled or when ordering a new item. In addition, devices like Show will allow Amazon to better leverage its strength in analytics to cross-sell the customer in the same fashion as the website, by showing the ubiquitous: “Customers who bought this item also bought…” options, providing Amazon more control on margins and power in the market—Tony Rodriguez, CTO, Digimarc Corporation 

As we saw briefly this year with WannaCry, AI and machine learning technologies are diversifying hackers’ arsenals so that they can create more sophisticated attacks – and this will only become a more common trend in 2018 as adversaries look to bypass basic protection methods like two-factor authentication (2FA). Next year, it’s time for organizations to start thinking beyond the basic layer of 2FA and start considering what’s next for safeguarding our systems and social platforms. Enterprises must begin adopting automated security tools on a broader scale to analyze their digital presence for threats and suspicious behavior, which will in-turn spur an interesting AI vs. AI dogfight—Phil Tully, principal data scientist, and Zack Allen, manager of threat operations, ZeroFOX

In today’s noisy digital environment, personalization in marketing will continue to be a priority and major theme. I expect that we’ll see AI and machine learning technologies play a larger role in making marketing messages and online shopping experiences more customized for each individual consumer. With the amount of customer data available, targeting the right people with a relevant message, offer or promotion in a timely manner is quite difficult, but machine learning and AI techniques are helping marketers correlate and synthesize signals from different sources, identify behavioral patterns and infer the strength of interest or purchase intent more efficiently than before. This will help companies get closer to the desired 1-to-1 marketing that is so hard to achieve and scale—Bryan Chagoly, VP of Technology, Bazaarvoice

AI won’t replace jobs in 2018 – it will augment them. A common misconception is that the rocket-like adoption of AI applications will replace human jobs in 2018. In cyber security, however, we can expect the opposite. AI will act as a force multiplier, helping humans allocate resources effectively and spend their time on the most important priorities. With over one million cyber security positions unmanned in 2016, there is an important gap to be filled. 2017 showed us that security teams simply can’t keep – in 2018, organizations are taking back the time advantage by using AI to autonomously respond and mitigate threats in real time, before they do damage—Justin Fier, Director for Cyber Intelligence and Analysis, Darktrace

[Bonus Update]

In 2018, we will see greater specialization of AI-powered technology in response to demand for more personalized decision-making and admin support that can augment individual work flows. It’s the little decisions that support our best work – organizing calendars, tracking to-do lists, scheduling meetings – that we will derive true value from the intersection of AI and enterprise communications. AI-powered tools will learn preferences and behaviors, and subsequently bend toward individual work flows, creating more specialized experiences and improving productivity for all–Keith Johnson, CTO, Fuze

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