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Data, data, data

Much like business transformation, data is not a new concept but how businesses use it will be the key to whether they sink or swim. Those that understand it to enact continuous improvement and change will be the ones that survive. This is because of its single source of truth and it will be this that continues to fuel the fire for areas such as AI, chatbots and machine learning technologies.

James Woodall, Chief Technology Officer at Intoware

We will start to see technologies enable partial automation of a variety of tasks

Automation occurs in stages. While full automation might still be a way off, there are many workflows and tasks that lend themselves to partial automation. In fact, McKinsey estimates that “fewer than 5% of occupations can be entirely automated using current technology. However, about 60% of occupations could have 30% or more of their constituent activities automated.”


We have already seen some interesting products and services that rely on computer vision and speech technologies, and we expect to see even more in 2019. Look for additional improvements in language models and robotics that will result in solutions that target text and physical tasks.


Rather than waiting for a complete automation model, competition will drive organisations to implement partial automation solutions and the success of those partial automation projects will spur further development.

Ben Lorica, chief data scientist at O'Reilly Media, Inc. and programme director of the Strata Data Conference and the Artificial Intelligence Conference

Productivity increases for people – and machines

Artificial intelligence and machine learning will lead to the largest productivity increases we’ve seen in years, not just for people, but for machines.


AI and ML applications will enhance and transform the user experience by reducing both technology and human complexity. The line between human and machine tasks will change and more of the thinking tasks of every business and system will be driven by machine intelligence.


AI and ML will continue to leverage the influx of data to drive greater efficiencies and insights that will optimize both the apps and devices we use every day. PCs will be able to predict power consumption needs based on usage patterns while apps will continue to learn from user preferences and behaviours to deliver more personalised experiences.


Even large-scale enterprise systems will use AI and ML to drive greater automation and intelligence, making it easier for humans to gather insights or make strategic decisions based on data as we move from peta-scale to exa-scale to zeta-scale.

John Roese, President and CTO, Dell EMC

We have the ‘where’ and ‘why’ for AI: 2019 will give us the ‘how’

The opportunities and need for artificial intelligence and machine learning are well understood: with projects such as IBM’s Watson already showing its potential. With this groundwork already in place, 2019 will be the year where we see more real-world applications of AI, as businesses begin to ask the big questions around ‘how’ AI will impact their operations.


For instance, how will organisations determine what questions are used to train their AI implementations? How will they address potential ethical challenges, such as the introduction of bias into the equation? Will consumers ever truly trust the technology? 2019 will see businesses and academia working together to determine the answer to these questions: working towards a trusted approach for developing AI and allowing it to find its place in the mainstream.

Huw Owen, head of EMEA & APJ at Couchbase

Experience over youth

The human factor is of paramount important to successful AI and automation (AI&A) projects, but skills are scarce. In the next 12 months we will see a significant investment in training and resources, and much of this money being spent on retraining older workers to become data scientists and solution architects.


With technical skills so scarce, no real skills pyramid and little in the way of a recognised career path, we’ll see many of these ‘new’ experts being aged 40 and above, bringing their considerable experience and existing skillsets into their new role.

John Gikopoulos, global head of AI and automation at Infosys Consulting

We will see natural language processing enter the business workplace

Amazon Echo, Google Home, and Apple Homepods have brought connected assistants to the home. For the first time, voice interaction has become a mainstream method of controlling devices to play music, get basic information, and administer smart home devices.


However, these devices haven’t made much of an impact in business. My expectation is that in 2019, they will find their voices in niche business scenarios too, and that connected assistants will be interfacing to email, CRM systems, and diaries, to streamline processes and give a helping hand.


I’ve also seen one of our users creating an impressive solution that creates automated SQL queries out of natural language questions about data.

Matthias Golombek, CTO at Exasol

HR to see key benefits from AI

One business area in which AI can be a step change is that of HR. We are not talking about AI replacing the sympathetic ear of an HR manager instead AI’s unbiased algorithms and machine learning techniques can be leveraged to predict and learn possible outcomes based on masses of historical statistical data.


Hiring managers are often out of there comfort zone when hiring new candidates, with most making up their mind within the 60 seconds of the initial handshake. This leads to 39% of businesses admitting that the interviewing and assessment skills of their staff should be improved, according to The Recruitment & Employment Confederation, resulting in many missing that killer hire.


AI-based algorithms can rapidly scan large volumes of candidate CVs and internal employees to identify who not only matches the criteria for an interview but if employed are likely to succeed in the role. Post or during the interview process, AI can review transcripts, audio and video content to look for those missed signals that indicate a candidate who can succeed or fail and flag these to the hiring manager.


Many of the major talent acquisition vendors are already building out or have deployed AI teams to underpin their platform growth.

Dave Rogers, senior sales consultant at  Evaris

Will artificial intelligence replace human jobs? Yes

Get ready, thousands and thousands of employees will be replaced by a simple computer system. AI products and systems are now mature enough to do multiple jobs, not to mention they may be more accurate and efficient than humans.


My prediction for 2019 is that the call centre agents and first line product support will be totally replaced by automated engines and digital assistants, letting that field of work disappear by the close of 2019.

Dr Khaled Mokhtar, Senior  IEEE Member and manager of emerging technologies and innovation at Etisalat

AI text analytics to emerge for customer data management

In 2019 there will be a major shift in how AI is used to look for more useful and actionable insight from customer data. Whilst sentiment analysis can be a useful tool, there are issues with its accuracy and it doesn’t predict anything on the whole.


As Forrester and others have also noted, AI text analytics will become a more powerful, alternative tool. This is because it classifies customer data by using actionable concepts and intent markers rather than basic keywords, giving a much clearer picture of the customer experience.


Contact centres will also adopt more AI to unlock complex sets of omnichannel interactions to understand what and why customers call, making it a key focus for CX in 2019.

Dan Somers, CEO at Warwick Analytics

AI needs to become more broadly available in business

As AI becomes more prevalent across industries, there is a growing need to make it broadly available, accessible, and applicable to engineers and scientists with varying specialisations.


Engineers and scientists, not just data scientists, will drive the experimentation and adoption of deep learning in industrial applications. Complexity of larger datasets, cloud computing, embedded applications, and bigger development teams will drive solution providers towards interoperability, greater collaboration, reduced reliance on IT departments, and higher productivity workflows.

Jos Martin, senior engineering manager at MathWorks

Businesses need to act now to fill the incoming voice technology skills gap

Voice technology risks becoming the next big IT skills gap and a real barrier to innovation. The value of the market is forecast to reach $8.30bn by 2023 – but this rising demand is set to have an impact as early as next year.


While voice technology has been around in the consumer world for the past few years, enterprise adoption is the next major focus for organisations. It will impact every technology interface and could transform the employee and customer experience.


But our research found that the available talent pool to support this innovation will soon be exhausted, with salaries and day rates rising significantly as candidate availability becomes stretched.

Businesses need to get ahead of the potential talent shortage by targeting those with adjacent skills in coding languages like C, C++, Java, and PHP.


Employers must look both within and beyond their businesses for talent and consider cross-training those with relevant coding skills to fill the anticipated void in voice technology talent.

Martin Ewings, director of specialist markets, Experis

AI to combat gender and racial bias

Contrary to most reports, AI can be a force for addressing gender and racial bias in 2019. If implemented correctly, the technology is far fairer than humans. We all have unconscious bias, which cannot be controlled and, in most cases, is extremely difficult to interpret. Its human nature to like what we know, and place value in our own strengths. Shockingly in the modern age, referrals remain the number one source of hires – proving that a form of nepotism remains rife.


Al, on the other hand, can be audited, giving HR departments tangible insight into bias and why hiring decisions are made. While Amazon’s tool has been widely condemned, the faults in the system were discernible in way that is impossible to interpret from humans. Amazons found its tool was downgrading CVs with certain words– how many of us could offer that level of analysis after reading a CV or conducting an interview?


Having this granular level of accountability can, in turn, help combat lawsuits and inform internal policies. If you can prove that no bias was present, or point to how potential flaws have been mitigated, it becomes nigh on impossible to sue. Policies too can be governed by such insight – why are so few applications coming from women? Why is aggressive and singular wording preferred? And crucially, how can these trends be reversed?

Ben Chatfield, CEO and co-founder at Tempo

Machine learning will manage your cloud for you

There’s a huge swing in the cloud market towards tools that allow you to effectively monitor and govern your cloud environment. Machine learning algorithms will soon be predicting the behaviour of your environment. Rather than waiting for a server to fail, companies will have trend analysis built in to create a profile of the behaviour of their solutions to see what’s going wrong. It will be able to predict peaks in usage, performance degradation, and see failures coming up. As a result, 2019 will see the industry moving towards self-healing cloud.

Stephen Long, OBE MD (Enterprise) at KCOM

Data intelligence and insight to see the biggest growth

Intelligence and insight are going to get even bigger in 2019. I’m not just talking about cutting-edge developments in areas such as AI and machine learning but adding increased intelligence to the whole IT estate.


More and more solutions now offer telemetry that can help with predictive maintenance and support – for example, printers that can order their own toner. We now have more data than we know what to do with; the big trends moving forward will be turning that into insights and using it to improve operational efficiency and user experience.

Craig Lodzinski, chief technologist for developing technologies at Softcat

RPA comes out of AI’s shadow

Robotic Process Automation will move from the shadow of artificial intelligence. Rather than buying into the hype around AI, businesses will realise the significant benefits of RPA, which is based on the notion of AI but much more accessible.


Unlike AI, which demands significant time and financial investment, RPA is easier to access, expand and scale, and will allow businesses to plan and test the software in order to see the impact it has on its operations and staff. This is a great indicator of the benefits large-scale AI deployment could bring in the future, but without the fear of large-scale failure.

Dean McGlone, director at V1

Embracing attainable AI

Much of the popular media focuses on the poster children of AI: the self-driving car and the AI doctor. These initiatives are exceedingly complex to get right and require billions of investment.

Rather than be intimidated into inaction, organisations should examine many more feasible applications of AI.


Having focused on studying 40 applications of AI, at Tribal we have been able to see that several are within the grasp of those with modest budgets.


In 2019, we will see hundreds of small AI-driven improvements in digital tools we use, e.g. suggestions of what we might be looking for, or about to do next, to make systems easier to use. Many of these will provide personalised responses by comparing tiny clues in our behaviour to that of others.

Andrew Liles, chief technology officer at Tribal Worldwide London

AI will die in 2019

Businesses are over 'AI'. The hype cycle burns faster these days and AI is experiencing a decline similar to what’s happened to the IoT. The joke going around Silicon Valley right now is that you get kicked out of a pitch if you bring up AI.


This is because AI, at the level of market perception, is unachievable by the vast majority of organisations. The challenge is that you not only need data scientists that are being hoovered up by the likes of Facebook, Google, Microsoft, etc., but you also need huge, richly codified training data and most companies are struggling just to connect their own customer data.


In addition, most of the buzz from software companies such as IBM and Salesforce amounts to nothing more than the mere evolution in natural language processing. All this means is that we are now really good at text-to-speech and speech-to-text, allowing us to create chatbots and recognise written content from interactions. What we do with that content once it’s wonderfully transcribed from voice still needs to be developed.


To caveat that though, AI is meaningful and has changed everything, including its ability to interrupt every digital record that we’ve ever created. However, it still has a long way to go to take people’s jobs -- it’s unlikely AI will aid professions like marketing in a way that is accurate enough that they'll even bother. Try uploading an image and seeing how well Watson or Adobe's Sensi really does. One of my favourite examples being, ‘Is it a Chihuahua or a muffin?’


Considering this, I think AI is dead...or at least we'll stop talking about it in 2019 with empty statements and start talking about business problems and business outcomes again…I hope.

Darin Archer, CMO at Elastic Path

Businesses will invest in AI solutions that can generate ROI

Companies will start demanding better knowledge of the ROI of their AI investments. They will be looking for a more accurate way to measure AI’s impact on the bottom line and customer experience.


This starts by considering your unique data acquisition situation. What data do you have and what data you can get? What data do you not have, that you need to solve for? And they will look for new ways to leverage their existing AI investment by blending AI and human touch—identifying where AI can support humans in their daily roles, and when to transition from a machine-driven interaction to live person for a better outcome.


Bottom line, if you’re asking how to deploy more AI, you’re asking the wrong question.

Thomas Hebner, head of product innovation,  Nuance Communications

From subjective decisions to objective discovery

2019 will of course herald more AI interest. But over the last couple of years, too many companies have had their fingers burned by choosing the question AI will answer, rather than giving it the freedom to answer the questions they had not even thought to ask.


These companies have, in other words, applied data analytics thinking to AI, and constrained its potential in the process. In 2019, we will likely see far fewer subjective decisions on where AI can be applied, and instead a greater focus on objective discovery.

Julian Box, Founder and CEO at Calligo

1/3 of organisations adopting AI will hire more IT staff in the next 6 months to keep up

The need for specialised skills to work with AI and automation technologies will drive a huge hiring spree in 2019 across the world – in Europe and the US, one in three businesses will need to hire more employees in their IT departments to accelerate their tech offerings in 2019.


Across industries from manufacturing and healthcare to non-profits, government, and financial services, the biggest challenge will be the same: upgrading their IT infrastructure and replacing legacy systems without failing on their digital transformation efforts.


In order to achieve this, businesses will need to invest time and money into sourcing the best talent with the best skills for the job, or risk falling behind the competition.

Neil Murphy, global VP at ABBYY

Chatbots and AI will extend beyond departmental silos

In 2019, we foresee that chatbots will be rolled out in more strategic ways. 2018 has seen companies adopt chatbots as tactical projects or as proofs of concept (POC). As their value is proven, more strategic approaches will be taken to broaden AI implementations across the rest of the organisation and customer base.


Chatbot projects will also move out of the siloed departmental approach as businesses see the potential to engage with customers across multiple touch points via chat. The transformative power of conversational AI will increasingly become a reality.

Cathal McGloin, CEO of ServisBOT

Commodity AI service providers on the rise

As with traditional IT services, we are likely to see companies stepping away from single enterprise funded development (due to its inherently high cost) and towards standardised commodity AI cloud offerings from the likes of AWS and Microsoft Azure – defining an increased level of maturity in the delivery model.


This will of course mean the “siloing” of more complex AI offerings with the big providers.

John Buyers, partner at Osborne Clarke

Significant leap in AI adoption

I’ve reached the conclusion that AI is not dissimilar to a New Year’s exercise or fitness regime – everyone is talking about it, but very few are actually doing it. Despite many early adopters reporting impressive ROI and much greater insight into their customers, AI has still been relatively slow to take off.


But I still think 2019 will see a significant leap in AI adoption. This is because solution providers are tailoring their offering to suit specific sectors much more than they have been, and also collaborating with others that have a deep understanding of particular industries. We recently worked with our partner Synpulse to create a Commercial Underwriting app. AI works best when used to address a specific challenge in a particular industry and this app is a great example of that, allowing underwriters to optimize, automate and improve the entire underwriting process.


So for 2019, AI will come in a range of different applications that meet either a certain business requirement or a specific industry requirement, from GDPR and credit risk to manufacturing and wealth management. Each application can deliver almost instant ROI, allowing AI projects to build momentum internally, as other departments and business units see how their challenges can be addressed with AI.


Which other applications will emerge is harder to predict, but I firmly believe that the future of AI in 2019 and beyond, will be based around addressing specific issues, and that one day AI as an application will be the de facto standard for how organizations use it.

Dr Dorian Selz, CEO at Squirro

Organisations must overcome analysis paralysis

In 2018, AI had the 'salted caramel' effect: everyone is trying it but not everyone is convinced. In 2019, those with a true vision, supporting strategy and solid implementation for the technology will reap the benefits.


Businesses should look to further embrace automation and technology that can orchestrate people, processes, robots, smart devices and secured systems together. Organisations that run on connected and intelligent systems will maximise their customers' experience and operational excellence.


According to IDG's Future of Work survey, three-in-four organisations are already deploying some form of intelligent automation. However, the maturity, complexity, and success rate of these AI projects vary widely. Despite the widely acknowledged benefits, few business executives and IT staff are experts in AI and many remain sceptical.


Over the next 12 months, organisations must overcome this 'analysis paralysis' to help the UK compete and make its claim as a global leader in AI technology.

Paul Maguire, vice president of EMEA at Appian

From the cloud to AI

The drive towards AI will become much more of a focus for businesses next year, particularly as companies begin to realise the huge benefits in efficiency when it comes to building and deploying applications in the cloud. Take Microsoft, for example; increasingly its customers are using Azure AI to build apps that are smarter, more intuitive and responsive in order to free up people power, and we will see more of this in 2019.


Businesses utilising the cloud will do well to leverage the mantra that ‘knowledge is power’, and applying predictive analytics to data that helps drive AI can mean companies can act on it and get ahead of the game. Working with a tech partner that has the technical capability to gather this data as well as provide consultancy of how it is used will be highly influential in helping organisations drive the benefit of AI in their businesses.

Gregg Mearing, head of managed services at Node4

Pretenders to fall away

2019 seems as if it will be the year of analytics, machine learning and AI. These tools are already available, though their take up has often been delayed by a failure to match these new capabilities with appropriate new workflows and SOC practices. Next year should see some of the pretenders – those claiming to use these techniques but actually using last generation's correlation and alert techniques in disguise – fall away, allowing the real innovators in this field to begin to dominate.


This is likely to lead to some acquisitions, as the large incumbents, who have struggled to develop this technology, seek to buy it instead. 2019 is the year to invest in machine learning security start-ups demonstrating real capabilities.

Stephen Gailey, solutions architect, Exabeam