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Artificial intelligence (AI) is invading our everyday lives, but it’s not as scary a concept as people once thought. AI has shown it can make our personal lives much easier, but it doesn’t stop in our homes. Businesses are constantly coming up with new ways to use top AI trends to engage with customers, make processes easier and drive sales.
We’ve already seen the popularity and effectiveness of AI-powered chatbots in recent years and how Facebook uses artificial intelligence to improve the results of ad campaigns. But what’s next for AI and how can it further boost the success of businesses in 2019?
With an increasing percentage of stakeholders professing their commitment to leveraging this technology within their organizations, we are sure to see transformation business value being derived through AI in the coming years. As we come to the close of 2018, let us gaze into the crystal ball to see what AI trends will rule in 2019:
More advanced AI assistants
Thanks to Siri, Alexa and other devices released by tech giants like Apple and Amazon, consumers have been enjoying the benefits of AI assistants in their home. You can ask AI assistants to play you a song, tell you the weather, and search out information online, turn off your house lights and much more. In fact, in a study from Adobe Analytics, 71% of smart-speaker owners reported using them at least daily, while 44% said they used them multiple times a day. This data proves that in 2019, more advanced AI assistants will be present in the homes of consumers, as well as their workplace and other areas.
Currently, consumers use AI assistants to carry out extremely mundane tasks like searching for a nearby cafe. However, AI assistants will soon be able to provide a more personal experience as they get more advanced at recognizing voices.
AI-powered recruiting tools
According to a survey from Indeed, 42% of employers polled were worried that they wouldn’t be able to find the talent they needed. For many businesses, the recruiting process is one of their most time-consuming and stressful tasks, but with advancements in artificial intelligence, AI-powered recruiting tools will be a recruitment trend to watch for in 2019.
For example, Mya, which stands for “My Recruiting Assistant,” is a chatbot recruiting assistant. It can communicate with candidates via Skype, email or text. It can pre-qualify candidates for you and even reject a candidate if you decide to pass on his or her application.
Along with AI-powered screening and candidate-communication tools, a number of emerging artificial intelligence tools are emerging that will help employers save even more time and find the candidates they need next year.
Conversational AI-powered search
Because users will soon start using AI-powered assistants in new ways and more often, advanced conversational AI-powered search will be a huge trend. With the introduction of voice search, the way in which consumers search online has changed. Instead of typing in a search query like “condos for sale Dallas,” consumers will be able to speak their search queries using a more conversational phrase, like, “What condos are for sale in Dallas for under $150,000?”
In other words, the way users are provided answers to their queries will become more advanced as well.
Continuing with the condo example, AI-powered search engines will do more than just providing users with a number of listings; they’ll also receive more conversational answers. Search engines could follow up with questions to provide more detailed solutions by asking, say:
- How many bedrooms do you want?
- What neighborhood would you prefer to live in?
- Would you prefer a gym and pool on the premises?
Users will then be able to narrow down the solutions and get exactly the search results they’re looking for. Since consumers are changing the way they search, the quality of the results they expect to get is changing, as well, pushing AI to keep up with those expectations next year.
Better conversational chatbots and virtual agents
Chatbots have been improving customer service for businesses of all types in recent years; you can even order a pizza through a Facebook chatbot now. In 2019, expect chatbots to become even more advanced and human than before. With natural language programming, you no longer have to have a robotic conversation: Consumers can speak to chatbots just as they would a live chat agent. Beyond simple chatbots, more companies will also be implementing life-like animated virtual agents, too.
Autodesk recently unveiled its virtual agent, Ava. Ava is a “digital human” who can answer customers’ questions, direct them to content and help them check out, as well as respond interactively to emotional signals from those users.
More and more retailers and businesses will be using conversational chatbots and virtual agents to solve customer service issues without having to pass users off to a real-life staffer.
AI will accelerate the democratization of BI:
AI is remaking the business intelligence market inside and out. Over the past few years, one of the core BI trends has been the convergence of the technology’s traditional focus on historical analytics with a new generation of AI-infused predictive analytics, search, and forecasting tools that allow any business user to do many things that used to require a trained data scientist. In 2019, more BI vendors will integrate a deep dose of AI to automate the distillation of predictive insights from complex data, while offering these sophisticated features in solutions that provide self-service simplicity, in-memory interactivity, and guided next-best-action prescriptions.
AI benchmarking frameworks
Evaluating the comparative performance of different stacks of AI software, hardware, and cloud services is exceptionally difficult. As the AI arena shifts toward workload-optimized architectures, there’s a growing need for standard benchmarking frameworks to help practitioners assess which target stacks are best suited for training, inferencing, and other workloads. In the past year, the AI industry has moved rapidly to develop open, transparent, and vendor-agnostic frameworks for benchmarking and evaluating the comparative performance of different hardware/software stacks in the running of diverse workloads. The most promising of these initiatives is MLPerf, as judged by the degree of industry participation, the breadth of its mission, the range of target hardware/software environments it includes in its scope, and its progress in putting together useful frameworks for benchmarking today’s top AI challenges.
Development of AI-optimized hardware and software
Ubiquitous and all-pervasive availability of AI will require paradigm shifts in the design of the hardware and software that runs it. In 2019, we will see an explosion of hardware and software designed and optimised to run artificial intelligence. With the increasing size and scale of data fueling AI applications and even more complex algorithms, we will see a huge demand for specialised chipsets that can effectively run AI applications with minimal latency. Investors are showing heavy interest in companies developing GPUs, NPUs, and the like – as demonstrated by Chinese startup Cambricon, which stands valued at a whopping $2.5 billion since its last round of funding this year. End-user hardware such as smart assistants and wearables will also see a massive increase in demand. Traditional software paradigms will also continue to be challenged. Today’s novel frameworks such as TensorFlow will become de rigueur. Architectural components such as edge computing will ensure that higher processing power is more locally available to AI-powered applications.
‘Citizen AI’ to be the new normal
One of the reasons we saw widespread adoption of analytics and data-driven decision-making is because we built applications that democratised the power of data. No longer was data stuck in a remote silo, accessible only to the most sophisticated techies. With tools and technology frameworks we brought data into the mainstream and made it the cornerstone of how enterprises plan and execute strategy. According to Gartner, the number of citizen data scientists will grow five times faster than the number of expert data scientists. In 2019, I expect Citizen AI to gain traction as the new normal. Highly advanced AI-powered development environments that automate functional and non-functional aspects of applications will bring forward to a new class of “citizen application developers”, allowing executives to use AI-driven tools to automatically generate new solutions.
Rediscovering and bringing human expertise back into the loop
Machine Learning is exceptional at data analysis to create models that recognize patterns, automate decisions, and make predictions it lacks in human reasoning abilities. In 2019, enterprise AI honchos will rediscover digital decision platforms and knowledge engineering to encode and extract rules and build knowledge graphs from their expert customers and employees. Knowledge engineering’s strength is human wisdom, and Machine learning employs data to drive decision making when used together, enterprises can dramatically accelerate the development of AI applications.