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More Industries to Embrace Machine Learning

Today AI is more of a trendy buzzword than practical reality, and it’s difficult to execute because AI is only as good as its data. While data integrity still varies within the enterprise, true implementation of AI is still a concept that will not come to fruition for a few years.

However, we’ve seen early stages of machine learning applications in verticals such as advertising and retail. In the years ahead, we’ll see more industries, including industrial IoT, digital health and digital finance, begin taking advantage of machine learning within applications to provide more meaningful user experiences.

Throughout this transformation, the database will play an instrumental role by accommodating rapidly-changing data at scale while keeping big data sets reliable and secure. 

Ravi Maruyam, CTO, Couchbase

The AI Hype Fog Will Clear

Artificial Intelligence hype will pass its peak. AI isn’t new but it’s grabbed the C-suite’s imagination and their budgets this year like never before.

All too often, though, the projects have been box-ticking exercises in an AI arms race. 2018 will see the fog of hype clear and the C-suite demand a more demonstrable return on investment. 2018’s biggest winners will be the projects where Artificial Intelligence augments people’s ability to recall or research information and process data.

Some of the biggest industry opportunities are in customer support applications where you need to make access to information quicker and easier, either for the customer or for the service and sales teams speaking to them. These applications are a long way removed from robots and chatbots and will move Artificial Intelligence closer to its goal of automating data and knowledge retrieval.

Heather Richards, CEO, Transversal

Businesses to Embrace AI as a Force for Good

AI and automation is set to transform every corner of the business world in 2018, and we can expect to see more organisations recognise the positive disruption that automation can bring. For many businesses currently, AI and automation is seen as a considerable threat. 

However, next year, AI will increasingly be seen as a force for good in business, and something that will only adapt jobs – and even create news ones, as Gartner suggests. Perceptions are already changing, albeit slowly, in a wide range of industries including finance, with global research from Sage revealing that accountants have a huge appetite for automation. 

The good news is some finance departments have already quenched their thirst for automation. Purchase Invoice Automation (PIA), for example, has become a key part of many organisations finance transformation plans. Next year, we can expect to see more organisations automating financial processes, removing mundane tasks that can be effectively streamlined by disruptive technology. These time savings will free up staff to focus on more high-value, strategic roles – such as ensuring the finance team provides the data-driven insight to the rest of the business about new opportunities and trends, so that businesses can take informed decisions based on the numbers.

Dean McGlone, director, V1

Seeing the Value of Data

Using modern business analytics, like AI and machine learning (ML), can massively increase productivity. It can make work more efficient through defining better processes, reducing manual data work, and getting real time decision support information into the hands of employees. This is something the UK in particular needs, as highlighted in The Chancellor of the Exchequer’s recent budget. 

That is one way the value of data can be delivered, making the Chancellor’s planned investment in AI and maths education welcome. However I see another aspect of data value that warrants attention.
Companies like Google, Amazon and Facebook are built on assembling and understanding data. They have multi-billion dollar valuations. Many of the software systems that they use to manage and understand this data are open source, available for free. That indicates that the unique data they hold, which trains their systems and their algorithms, has intrinsic value.

With such clear examples of data value, I believe that in 2018 investors and hence boards need to start to look at ways to attribute a tangible value to an organisation’s unique data, and the algorithms that analyse it.

James Petter, VP EMEA, Pure Storage

AI Comes of Age in Cybersecurity

2018 will be the year that Artificial Intelligence (AI) comes of age in cybersecurity terms. AI will grow in every area. The detection of insider threat is becoming artificially intelligent by monitoring the way in which people communicate and the growth in demand for an automated AI approach will continue.

In 2017, we saw the likes of Wannacry create havoc across almost every market sector and we will see the emergence and fast adoption of what can best be described as the next generation of anti-virus software that will use AI to learn how a virus works on your network and deal with it accordingly. 

Chris Farrelly, general manager, HANDD Business Solutions

The AI Era Could Present a New Opportunity for Women

The introduction of AI in the workplace has the potential to automate various processes in many modern organisations. As operational roles will become automated, AI will see a shift in the need for day-to-day transactional tasks to more creative work. 

This shift will mean the demand for soft skills and a more ‘human touch’ will rise. This in turn will present new possibilities and opportunities for success for business. As softer skills are often associated with women, the AI era could present a new opportunity for women in the workplace.

At Yolk, we have noticed an increase in demand for candidates with both soft and technological skills, from entry-level jobs in the IT sector right up to CIO level.

The AI era therefore may bring with it more gender equality in the workplace with possibly a higher percentage of women in leadership and board positions. However, rather than feminising the workplace the AI era will be about men and women improving their interpersonal skills to make themselves more employable. 

Mohammed Ahmed, head of IT, Yolk Recruitment

The Rise of the Intelligent Application

In the artificial intelligence and machine learning space, in 2018 we will see the rise of the intelligent application. A surprise from 2017 is the realisation that while these applications are beginning to become more mainstream, they are actually already among us and are only going to continue to get more prominent in our workflows. Also in 2018 there will be widespread enterprise adoption of a standard workflow for building artificial intelligence applications. This will continue to push AI enabled applications into the mainstream.

Matthew Farrellee, emerging technology & strategy, CTO Office at Red Hat

AI to Solve Complex Engineering Problems

The future of business requires artificial intelligence. In 2018, I expect AI techniques to be applied to solve more of the complex engineering problems organisations face in design, testing and certification of engineering products. By utilising 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.

Moreover, while neural networks have existed for decades, only now is massive computing power available at a reasonable cost, which in turn has helped increase the number of layers in these networks.

Each layer adds more intelligence but also consumes enormous computing power, which used to be prohibitively expensive. More layers mean better outcomes. Over time, AI and machine learning will become smarter about analysing data and making discoveries quickly that can positively affect businesses’ bottom lines.

Mohit Joshi, president, Infosys

A Backlash Against AI Hype

We will see multi-faceted developments, including an explosion of supply side investment, some investor disappointment and a backlash against the ‘hype,’ concentrated around protest against the impact of AI on jobs.

Underneath all of that, there will be some incredible developments in the application of AI in important parts of society. As we re-wire businesses and institutions to take advantage of the ‘new machine’, we have unprecedented opportunity to make things – including work – better. AI will help doctors become better doctors and teachers become better teachers, through supporting them and taking away some rote tasks. AI won’t destroy jobs, but make them more effective, productive and satisfying. Human imagination, wants and needs are inexhaustible – AI will help us imagine and create the next level of work from which the vast majority of people will benefit.

Ben Pring, vice president, Cognizant, and director of the Center for the Future of Work

Healthcare to See Massive Disruption

AI has the potential to cause massive disruption in the pharmaceutical and healthcare industries. It’s relatively early days yet, but over the next year we are going to be making a lot of comparisons between human and AI-driven discoveries and decision making. This is inevitable as we try to work out whether AI is ‘better or worse’ in different situations.

This journey – finding areas where AI is good enough to work in parallel with, or even take over from humans – is one that we will be on for a while. Currently, although life sciences R&D generates huge volumes of data, and this is supplemented with mhealth and IoT data from healthcare, data formats vary wildly – a lack of data standards will need to be addressed.

In the future, for example, it will enable scientists to more easily identify and map molecular pathways that underpin diseases, helping to accelerate the development of personalised medicine.

Nick Lynch, consultant, The Pistoia Alliance

Scientific Research to See Productivity Boost

We are going to see a radical change in 2018 and beyond as AI techniques both become more productive, and tools become more transparent and user friendly.

This will have a particular impact in scientific research and publishing, improving productivity and efficiency. Recent research from Stanford University found that since the 1930s, the effective number of researchers at work has increased by a factor of 23, but productivity has actually declined.

AI will help to overcome these barriers – improving outcomes for humanity by helping researchers to solve the problems we face globally in diverse areas – from antibiotic resistance, to environmental degradation and climate change.

Jabe Wilson, consulting director, text and data analytics, Elsevier

Business Voice Assistants to Finally Emerge from the Lab

Siri, Alexa, Cortana, Google: enabled by rapid advances in voice recognition and artificial intelligence, voice assistants have become a key consumer technology. 

But voice assistants have been slower to emerge in business applications, as they pose unique challenges: access to disparate enterprise data and deep understanding of business context and processes. This becomes apparent if we consider the complexity and domain knowledge required to execute an instruction such as: “Get all documents and set a final review of product X launch.” Such basic tasks are in fact quite complicated and highly variable between different industries, companies and even individual projects. 

Yet, voice assistants in business hold the potential for far greater productivity and economic impact, especially when coupled with UCaaS, and further integrated with team collaboration and contact centers. Consider the power of having a business voice assistant as a virtual participant in a team collaboration workspace, including participation in conference calls.

It can be available to retrieve documents and information at everyone’s request, and over time I see it beginning to proactively offer assistance based on the collaboration context. 

Scott Hoffpauir, CTO and co-founder, BroadSoft 

Businesses to Selectively Apply AI to their Operations

Artificial intelligence is still very much in its infancy. Despite all the hype, no AI technology has yet passed the Turing Test - a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human.

But the advances of faster computing multiplied by advances in algorithmic computing – Machine Learning or AI - have been breath-taking. While AI-driven solutions have been great at correlation none of them has yet mastered causation, and AI technologies are not yet that applicable in everyday business situations.

The average business doesn’t have the resources available like Amazon with Alexa. But they need to apply AI driven solutions to specific elements of their own business – the efficiency driven approach of deploying AI. Approached in this way, AI can have a massive impact for any business, deepening customer understanding to prevent churn and increase loyalty is a great example.

Dorian Selz, CEO, Squirro

AI to Become Integral to Driving

AI will soon offer the ability to repeat actions consistently and quickly. It’s in these areas that AI will start to change the way we drive.

Tomorrow’s connected car will generate huge quantities of data; estimates suggest up to 25GB a day could be sent from a car every day. AI can sift through these massive amounts of data – crucially data that drivers typically don’t have access to or could not access without being distracted – and help to take stressful actions away from everyday life for drivers.

AI could well optimise the driving experience with an emphasis on safety, convenience and comfort. Imagine a car that takes itself to the fuel station when it’s running low on fuel or a car that recognises your voice and adapts its actions because it knows who you are.

AI will also assist the car in providing context; it will respond to the weather or where you are and drive accordingly. Providing context makes interaction with AI more meaningful, more real.

We predict that as AI makes driving easier and less stressful, removing the pain points, AI will become an integral part of everyday driving.

Andrew Till, vice president, connected services, HARMAN

Chatbot Growth to Have Wide-Reaching Impacts

A place that we’ll all see the adoption of AI growing, and effecting, all of us is within IT. We can see this happening already with the growth of customer-facing conversational interfaces that give people support on many of the websites that they use on a day to day basis. For example, Spotify and Lyft interact with their customers via chatbots on Facebook Messenger.

In the next year or so we will start seeing chatbots like these cropping up more often within the enterprise, operating as the part of an IT solution which communicates with end users when they need support or new equipment. The automation of this communication and these processes will mean that users will be able to gain access to advice faster, outages and downtime will be reduced and, ultimately, we’ll be able to do our jobs more efficiently as IT will be delivered with the level of convenience we’ve grown to accustom, due to the speed associated with other parts of our life, like online shopping. 

All verticals will be affected by this shift, and organisations that deal with large quantities of data such as healthcare and finance companies will feel the difference the most as their day to day becomes more streamlined. AI is a crucial element of the transformation of IT which we are beginning to see, as IT grows from the department of 'no' into a business enabler.   

Ian Aitchison, senior product director – ITSM, Ivanti

Businesses Need to Invest Now to Stay Ahead of the Game

The usability and technological adoption of voice searches over the coming 12 months will determine how you plan your strategy, and where you start playing in the space. Realistically, Amazon and Google are going to be the two big players so you’ll have to consider SEO and AEO (Amazon engine optimisation) implications. This means taking into consideration how people talk, as well as how they type.

To stay ahead of the game, your business needs to invest in smart advertising and skill building – now.A great example of how this can work well for a company is Dominos (who now class themselves as a tech company). They are building skills within Alexa that are so user-friendly, customers don’t even need to move to get their pizza delivered to them anymore.

All they need to do is ask “Alexa, ask Domino’s to feed me”. If you’re able to imitate or learn from this model by considering how you can make your customers’ lives easier then you’re on to a winning formula, and have the potential to maximise your commercial benefit.

Liam Foy, head of social, Bring Digital

Retail to Embrace AI in 2018

In 2018 AI will allow retailers to understand customers’ preferences as well as their five closest friends do, if not better. AI will memorise their browsing pages, purchases, likes, clicks and most intimate wishes. While this might sound Orwellian, it also means you will be able to take a cognitive load off of your customers’ minds and offer a more pleasant customer experience.

AI in 2018 will also bring SEO-voice activation, which is an as-yet unexplored opportunity for online marketers. What if, rather than being overwhelmed by choice, your customer knows exactly what they want? All they need to do is take out their phone and talk to it. It is your job, however, to make sure that your business is SEO-optimised and comes up in top lists of voice search results. The applications of Siri and Alexa will become far-reaching. Even if your customers are not looking for anything particular, but are merely enquiring about the weather, their phones will be smart enough to suggest the timely purchase of an umbrella. Or 20 minutes later, when the sun re-emerges, a pair of sunglasses.

Retargeting ads will have real-time applications to benefit your business, and will offer important customer usability.
It seems like the evolution of AI will first be preceded with the evolution of actual intelligence in 2018.

Online marketers will be benefiting from unprecedented knowledge of their customers. By taking advantage of this knowledge, they will be able to guide their behaviour in desired ways more easily. This will be done by offering personalised real-time recommendations, enhancing cognitive biases, being interactive and generally bridging the gap between customer and salesperson. 

Philippe Aime, CEO, Convertize

Businesses to Use AI to Untangle Complex IT Systems

Companies are having trouble keeping up with consumers’ desire for innovation. Better, sleeker, faster seems to be in constant demand – and all with a flawless experience. But, old legacy apps weren’t built for this modern wave of digital users. They just don’t work at speed or scale – at least without performance issues that cause more abandon rates than signups. 

So, 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 – at least by using traditional tools. 

That’s why, in 2018, AI will become critical in IT's ability to master increasing IT complexity in order to deliver on consumer demands. Organisations 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

Customer Service: AI to Drive a Decline in Call Centres

According to a recent Forrester report, call centres will step aside so that artificial intelligence (AI), bots, and other intelligent self-service solutions can address customer-facing problems over the next decade. In fact, by 2020, it’s predicted that 85% of customers will manage 85% of their relationship with a business through AI.

We will see adoption of AI accelerate in 2018 as more organisations realise the significant rewards and as these disruptive technologies become more accessible.  

One example of a disruptive technology is AI-driven Billy Bot, a ‘robot junior clerk’, which will support the work of a traditional barristers’ clerk, identify what legal help people need and match them to the right legal representation. Integrating with MLC, Advanced’s chambers management software solution, the chatbot’s goal is when someone needs a lawyer or barrister, it can automate the process of finding the most suitable representation, know who is available at the right time, and manage the scheduling of appointments and attendance in court.

We’ll also see health service providers look to AI and automation to empower patients to self-help rather than contact an NHS service, helping reduce the number of patients who need to see a GP. Olivia, Sensely’s AI virtual nurse app, which is based on Advanced’s innovative Odyssey software, is already doing this.

The nurse gathers details by asking questions to the ‘patient’, just like a GP would in person, but the app then acts upon the information and provides specific actions and decisions based on answers given by the patient, to advise on the best course of action.

Jon Wrennall, CTO, Advanced

AI to Bring Increased Threats and Advanced Skills to Cybersecurity

In the security domain, we’ll start to see trickle-down effects in terms of artificial intelligence as we move forward. If you think about the hierarchy of those working in AI, you’ve got DeepMind at the very top, along with Google and other major companies.

They are all doing some seriously exciting, specialised intelligence work that is pushing the boundaries of what is possible through these systems. As these companies continue to innovate, the security industry will begin to use their more advanced techniques and systems to the benefit of our own products.

As we move forward, it seems that AI will also be used specifically to try and combat the skills gap in cybersecurity. It’s well established that there simply aren’t enough people with the requisite skills within the industry, so it’s up to vendors and their partners to supply these services or make their products as easy to use as possible, to minimise the technical skill needed to run them.

We’ll see a real move towards AI being made as simple and useful as possible for teams to use while the industry looks to address the skills gap.

We’ve already started to see a rise in the use of AI bots placing more targeted phishing adverts and emails, analysing large amounts of social media information to profile their targets. Online chat bots are also being seen more and more in use for customer service – therefore positioning them as a system that people trust.

Attackers will look to use this trust and build chatbots to try and obtain bank details from people – so expect a rise in the amount of malicious chatbots found on the internet.

Dr Jamie Graves, CEO and founder, ZoneFox

Effective Logistics to be Recognised as the Key Driver of Successful Machine Learning

Organisations will recognise that 90% of machine learning success is in the logistics, rather than the algorithm or the model.

Being able to effectively manage data is essential to running successful machine learning systems in the real world. This is true for the complete life cycle – from managing input data to the development of machine learning models, to their ongoing maintenance in production.

The good news is that with effective architecture and good planning, much of this can be handled at the platform level rather than the application level – and that cuts across many systems handled by different machine learning tools. In other words, you don’t have to come up with a new plan for logistics with every different project.

Because we think people will increasingly recognise the need for efficient machine learning logistics, we also think there will be a trend toward stream-based architectures and a global data fabric as part of their overall organisation.

Ted Dunning, chief application architect, MapR

AI to Take Over Mundane Business Tasks

Artificial intelligence enabled through cloud platforms will begin permeating across enterprises, industries and applications. While we aren’t quite at the level of HAL from 2001: A Space Odyssey, technologies like Alexa, Cortana and Siri are demonstrating the power and potential impact of AI in everyday life. 

For businesses, capabilities of machine learning, powered by petabytes of data and insanely fast compute resources will impact consumer experiences, biotech research, financial modeling and myriad other applications. Key to this is letting AI remove the mundane tasks and letting existing specialist human teams focus on other factors critical for business growth and development.

Paul Mattes, Vice President, Global Cloud Group, Veeam

Payments to See Significant AI and Machine Learning Growth

2017 saw a massive democratisation of AI technology with more accessible solutions from providers like Microsoft, which is undoubtedly driving adoption. In the payments space, we expect to see significant growth in AI and machine learning throughout 2018. Payment providers are already exploring new ways to adopt the technology to streamline processes, maximise acceptance and improve customer experience. 

One area we see a significant opportunity is for organisations to use AI not only to identify individuals who are likely to fall into arrears on payments, but also to intelligently tailor the time and method of communications to them based on what they know has resulted in action in the past. We also expect to see significant strides forward with fraud prevention, know your customer and anti-money laundering as current rules-based systems maximise AI and deep learning capabilities.

Growth of the technology is a certainty. While data and the understanding of it is key to the success of machine learning, what will standards such as GDPR mean for access to the building blocks?

Andy Davies, product and strategy director, Pay360 by Capita

AI to Drive Dominance of Intelligent Enterprise

AI skills, such as pattern recognition and decision making, played an important role in the much-talked about AlphaGo win against expert (human) player, Lee Sedol. The most ground-breaking technique AlphaGo demonstrated, however, was reinforcement learning, which is the tendency to produce an action that is followed by an increase in reward. Algorithms based on reinforcement learning are already available. In 2018, they will be applied to autonomous vehicles on the road and robots on factory floors.

Over the next year, interest in AI will grow across every industry. By 2020, the AI market will grow to $47bn. But how will these investments pay off for the enterprise? Equipped with AI and cognitive systems, big data analytics, and machine learning, the insights-driven intelligent enterprise will outpace its competition.

Better data will mean better algorithms, and better algorithms will mean better data, and so on. We will become much more productive as we offload collecting and processing data to AI systems. The intelligent enterprise will leverage agile development to build apps in the cloud, automate processes and menial tasks to optimise efficiency and explore data lakes for sophisticated insights and better decision making.

Mark Barrenechea, CEO, OpenText

AI Will Be Used to Augment Creativity

One of the more interesting and emerging uses of artificial intelligence is in creative processes. While many think of AI as lacking the same creative spark that humans have, we are seeing how algorithms and data can augment creativity, innovation and inventiveness. This will continue into 2018.

For example, we’ve seen companies use AI to write music for human composers in the past year and, at Iprova, we’re using our AI to help research and development teams invent new products and services faster and more effectively.

Due to the data explosion of the early twenty-first century and the convergence of previously unrelated domains, there are links between concepts that no single human inventor can know at any one time.

AI can remove the borders to invention created by R&D teams having only specialist knowledge, effectively augmenting their own insight with almost all knowledge imaginable.

We will see AI and algorithms increasingly used to cut through the abundance of data and find only the most relevant information. Some of the world’s biggest companies are adopting this approach and the technology has the potential to reshape how we think about invention.

Julian Nolan, CEO and founder, Iprova 

Data Science Will Break Free From Code-Dependence

Algorithms are a commodity, but enterprises are under increased pressure to turn analysis into insights and insights into action—and in the current data science landscape, too many analytic models are never deployed.

To address this challenge in 2018, we’ll see increased adoption of common frameworks for encoding, managing and deploying machine learning and analytic processes. The value of data science will become less about the code itself and more about the application of techniques.

As analytics becomes more pervasive in organisations, and the number of data sources and statistical languages (R, Python, Scala, etc.) continues to expand and evolve, we’ll see the need for a common, code-agnostic platform where LOB analysts and data scientists alike can preserve existing work and build new analytics going forward. Whether the user is no-code, low-code or code-friendly, this common platform will be key to making analytic models and applications easier to deploy for anyone in the enterprise.

Langley Eide, Chief Strategy Officer, Alteryx

AI to Augment the Human Customer Experience

A long list of bold statements have been made about AI over the last few years, with people stating that it will take over our jobs, the way we shop or even our household chores – or completely replace any form of human interaction.

The fact is, AI’s main value at the moment is in making people better and more efficient at what they do – especially when it comes to businesses communicating with their customers.

Next year, I predict that we will see AI put to real use not in replacing the human customer experience, but in augmenting it.
For instance, a transport company can use AI to power an SMS service or a messaging app like Facebook messenger gathering customer feedback – performing initial analysis so that the customer experience team can act on that feedback and improve services for the future, rather than spending their time contacting every customer who travels with the company.

Similarly, the financial sector can use AI to evaluate credit scores, so financial advisors can provide the customer with more accurate advice – without ever placing sole responsibility for advice on AI’s shoulders.

Whatever the use of AI, companies should not get overexcited about what the new capabilities will mean for the business, and ensure that they’re still communicating with their customers in the right way, at the right time and with the right message. Otherwise they simply run risk of alienating customers and appearing out of touch with what they want.

Antoine Hemon-Laurens, Customer Experience Expert, Quadient