AI in business is about to go through exponential growth in 2020, across numerous sectors and dozens of new use cases. With current uses for AI accelerating at the same time and becoming more commonplace, the future of AI and its impact on the world and the global business community is a positive one.
In this article, we look more in-depth at the latest technology trends and future uses of AI in business. Based on industry analysis, our work creating AI-powered conversational solutions, other AI services, and our expertise in this field, we predict the following to be the top 8 trends to watch for in 2020.
#1: AI-enabled apps making healthcare more affordable
Healthcare is a hugely expensive sector. It is only going to get more expensive, for governments, insurers, and payers (depending on whether you are in a country with state-funded healthcare). As populations age and lifestyle choices continue to make an impact on the healthcare provisions populations need, the financial cost is going to grow.
One AI future we and others expect to see emerge into reality is the positive impact of AI on healthcare. Health providers and pharma companies run on data. Patient care is data-driven. One of the most serious challenges is joining all of that data together and ensuring improved patient outcomes, reducing costs, and offering greater efficiencies.
With AI in business applications, there can be more efficient scheduling, optimization, automated reporting and workflows, post and pre-treatment care, and even real-time data flows to doctors and healthcare teams to monitor patients more accurately. These and other AI-powered innovations will, over time, make a big impact; reducing costs for providers and improving healthcare outcomes for patients.
#2: Natural Speech Recognition
Human language, speech patterns, dialects, and the meanings of words are incredibly complex. One of the biggest challenges in the AI space is giving AI-powered devices and software an equal level of understanding and comprehension as another human. Even if two people are speaking a different language.
Amazon, Google, and other tech giants continue to pour money into providing a comprehensive and near-universal solution for this problem. Numerous other startups, data scientists, and universities are working on this too. Bridging the understanding and comprehension gap would take AI another leap forward.
Natural speech recognition, also known as Natural Language Understanding (NLU), is the way AI will take this leap into the future. Once AI can understand human speech more accurately than it currently does, it will be more useful across a wider range of solutions; from customer service to complaints to sales and other more complicated tasks where humans and machines need to interact.
#3: AI consumes less data, learns quicker
AI development is heavily dependent on the speed at which data is consumed, processed, and integrated into algorithms. Getting access to the right kind of data, and often data that is clean and useful enough to power a new machine learning or AI-based system is one of the biggest challenges data scientists and companies in this field face.
One way around that is to use new data synthesis methodologies, which is another of the latest technology trends we can expect to see more often in 2020. What this means is it will take fewer data to create, test, and improve any new algorithm and system, making it easier to create new AI-devices and software.
#4: Improved AI neural networks efficiency
For AI in business to play more of a key role, new AI-powered systems need to mimic as accurately as possible how humans would perform tasks.
And yet the human mind is something we still don’t fully understand, so how can we create AI neural network architectures that could equal our abilities? Data scientists have been busy working on this for years and in 2020 more evidence in business and real-world use cases are going to become apparent.
We are likely to see more efficient, smaller, real-time neural network architectures running on smaller devices. In many ways, the first problematic example of this is already widely known thanks to the emergence of deep-fakes. It has already become a cat-and-mouse game, similar to online viruses, and is likely to continue into 2020 and beyond.
#5: Robotic Process Automation
Robotic Process Automation (RPA) is a standalone series of systems and it can be used alongside and integrated with AI and Machine Learning (ML). RPA is a way of automating repetitive and mundane tasks that are low-value, but essential. Tasks that can take hundreds of working hours could be done more efficiently with the help of automatic systems; AI and ML.
#6: Automated AI-driven risk management
Risk management is something that could result in better outcomes and be reduced risk with the support of AI-powered systems. In the financial services sector, the risk is already something that is largely data-driven, and with AI in business, we can expect to see risk analysis and new risk weighting methodologies use AI more extensively, reducing reliance on human risk analysts.
#7: AI-powered computer vision in the security
Surveillance cameras can now go beyond simply being aware and recording. With AI, they can monitor, alert, and provide a more effective analysis of security events and incidents in real-time. This includes tapping into facial recognition software and alerting security services. This is a growing sub-sector of security, one that MarketsandMarkets reports will reach $1 billion in 2023, with a CAGR of 7.40%.
#8: AI chatbots play a more proactive role in customer service
And finally, something we have seen growing in popularity and acceptance amongst consumers and businesses is the role of AI-powered chatbots. Across dozens of platforms and social networks, more chatbots than ever are being used in customer service and sales-related roles, even handling complaints. Thousands of companies around the world use bots on websites, another trend only set to continue into 2020 and beyond.
In business, AI, ML, and deep learning systems are playing an increasingly important and normalized role. In 2020 and beyond, these AI trends are going to accelerate, with much wider use of AI taking on a growing list of human tasks and moving staff into higher-value work.