Machine Learning and AI Predictions for 2019

Machine Learning and AI Predictions for 2019
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2018 was an exciting year! Data scientists became one of the most sought-after positions and as such, the market paid those professionals well. We saw the maturation of several artificial intelligence services, whether it be from companies such as IBM with Watson, or Microsoft with their Cognitive Services or Bing offerings.

With the holiday and festive season behind us, it’s a good time to look ahead to what 2019 may bring. In this blog post, we focus on machine learning and artificial intelligence predictions that might be in store for the year ahead.

Download our Machine Learning and AI Predictions that we believe will be key trends in 2019.

Increased Adoption of Services

Ok, so we alluded to this in our introduction, but we foresee an increased adoption of machine learning and artificial intelligence services such as Microsoft Cognitive Services by businesses.

We anticipate that businesses will take AI and machine learning proof of concepts and advance these into legitimate production use cases. We expect these solutions to enhance digital transformation initiatives that help organizations scale, remove process bottlenecks and continue to automate manual tasks or processes.

With a recent survey by Deloitte estimating that up to 57 percent of businesses are set to increase spending on AI services, one thing is for sure – 2019 will be no different!

[bctt tweet=”The growing adoption of AI services will contribute to increased automation, pushing manual tasks to be managed by exception.” username=”GAPapps”]

With this increased adoption of AI and machine learning services, and solutions can easily be integrated “out of the box”, we expect the size of IT departments to contract a little.

The adoption of AI services will contribute to increased automation and shift the focus from drilling down and analyzing reports to businesses being alerted to things that warrant their attention (driven machine learning).  Manual tasks will be managed by exception, thereby further optimizing business operation processes.

Explosion in Conversation as a Service

We believe the user experience will continue to improve when acting with digital agents and chatbots, powered by increasing advancements in natural language processing and voice recognition.  We also expect this area of artificial intelligence to grow and user adoption to increase.

With advancements in technology such as the Microsoft Bot Framework and Language Understanding Intelligence Service (LUIS), it’s becoming easier than ever to build intelligent conversational experiences.

In recent years the Amazon Echo and Google Home brought the digital assistant to the home. Voice interaction with AI-powered devices entered the mainstream and they’re so simple to use, that even children can use them.

That said, these devices, have struggled to make an impact in the business world. In 2019, we predict this will change, and voice devices will find their way into the enterprise. Connected assistants will interface with email and CRM systems to give businesses a helping hand.

For example, Alexa Apps could be built to interface with social listening tools such as Social Opinion, which lets users ask Amazon’s Alexa what the public mood is for their product or service, thereby giving businesses the ability to perform a  quick “temp check”.

Download our Machine Learning and AI Predictions

New Dangers

Security might not be the most exciting topic to think about when considering the year ahead but with the sheer range of advancements that have been made in AI and machine learning, it’s certainly worthwhile to take stock and think about.

In 2019, we believe that with the increased adoption in voice-enabled hardware such as Google Home, these devices will be subject to data breaches or inadvertent data sharing. Just like phishing emails and unscrupulous websites or software, we expect to see the introduction of new software or services to help mitigate these risks in 2019.

Automation and Transparency

Machine learning algorithms will continue to improve business processes in 2019, but they rely on unbiased and reliable training data to make decisions. With the increased adoption of online services and AI tooling, make no doubt about it, there will be organizations out there that try to manipulate the decisions a machine can make. Consider the “fake news” problems that Facebook experienced, where false news was propagated and surfaced directly into user walls, in effect, almost creating an echo chamber.

In 2019, we believe that while the problem will increase, we also predict that more intelligence software will be developed to track troll armies or “click farms,” thereby increasing the transparency of news stories or content shared online.

GDPR and Trust

The introduction of GDPR in 2018 was possibly one of the biggest things to happen in the information world last year. If 2018 was the year of GDPR compliance, 2019 will be the year when businesses and organizations get held accountable.

In 2019, we anticipate the ICO will start to take its first few high-profile audits to really see who is adhering the GDPR, thereby sending signals to industry that the GDRP must be taken seriously.

Talent and Education

For the last few years, the talent pipeline has struggled to plug gaps when it comes to data science, AI and machine learning.  It’s no surprise that as the technology moves so fast, the academic realm can find it difficult to plug the AI skills gap.

In 2019, we believe that universities will adjust their strategy when it comes to computer science degrees and it doesn’t seem like we’re alone.

Dr Greg Benson, professor of Computer Science at the University of San Francisco and the Chief Scientist at SnapLogic, also feels that “machine learning will soon be required in computer science degrees.”

[bctt tweet=”It’s no surprise that as technology moves so fast, the academic realm can find it difficult to plug the AI skills gap.” username=”GAPapps”]

Legislative Changes

One of the major airports in London, UK was recently brought to a standstill due to what was believed to be drones flying too close to protected airspace. In 2019, we believe that the IoT (internet of things) and connected devices will continue to grow but that governments will clamp down on the use of specific IoT devices.

We also predict that autonomous devices such as drones, robots or vehicles will make their way into the mainstream and interact more naturally with the human environment. Connected to the cloud and powered by AI, it wouldn’t be out of the realm of possibility for drones to operate a sort of “collective mind” or hive mentality and collaborate together to achieve a common goal such as clearing trash, harvesting crops or simply delivering packages.

With such advancements being feasible, in 2019, we expect the government to tighten up regulations to ensure that both machines and humans can work together safely in the environment they both share.

Download our Machine Learning and AI Predictions that we believe will be key trends in 2019.


In this blog post, we’ve looked ahead to 2019 and tried to arrive at some predictions we believe could make their way into the year we’ve got ahead. We’ve looked at everything from increased adoption, to conversation as a service, and how we believe that increased advancements in machine learning and AI have the potential to introduce new security threats and legislative changes.

Here at Growth Acceleration Partners, we have extensive expertise in many verticals. Our nearshore business model can keep costs down while maintaining the same level of quality and professionalism you’d experience from a domestic team.

Our Centers of Engineering Excellence in Latin America focus on combining business acumen with development expertise to help your business.  We can provide your organization with resources in the following areas:

  • Software development for cloud and mobile applications
  • Data analytics and data science
  • Information systems
  • Machine learning and artificial intelligence
  • Predictive modeling
  • QA and QA Automation

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