From ancient Greek mythology to Mary Shelley’s Frankenstein in the 1810s to Issac Asimov’s I, Robot in the 1950s, artificial intelligence (AI) has fascinated the human race endlessly. It is only after the big data era of the 1990s that AI began taking shape as a reality — far less dystopian, far more utilitarian. Two decades later, today, artificial intelligence has become ubiquitous, touching the lives of millions in myriad ways. If you’re an aspiring technology professional, here are the top 10 artificial intelligence trends that will shape your career.

Artificial Intelligence Trends You Must Look Out For

When we hear ‘trends’, we often think of it as the hype that will soon die down. But that isn’t always the case. In an emerging and rapidly evolving technology like artificial intelligence, trends are indicators of the direction the industry will take in the next few years — some may be immediate, some may have a longer life cycle. As an aspiring professional, knowing where your industry is headed is important to steer your career in the right path. Here are some artificial intelligence trends we observe both globally and in India. 

1. Artificial intelligence Trends: AI as a Service will gain popularity

The ‘as a service’ business model among technology businesses has been on the rise since cloud computing emerged. Simply put, it is the ability to use a product over the internet, without having to invest in building, customization, hosting, maintenance etc. Products like Salesforce or Freshdesk follow the software as a service (SaaS) model, Microsoft Azure and Google Cloud are platforms as a service (PaaS) offerings. 

In that vein, artificial intelligence as a service (AIaaS) is slowly gaining popularity. Companies are building AI products — like chatbots, APIs, customisation engines etc. — and offering them as a subscription service online. This way customers can plug-and-play AI instantly at affordable prices. As AI adoption continues to rise, we’ll see several startups building AIaaS products for a wide range of industry applications.

2. Artificial intelligence Trends: The industry will look for specialists within AI

AI Specialist is the #2 emerging job for 2020 in India, with companies across sectors looking for artificial intelligence professionals to perform specialized tasks within each industry. In manufacturing, this might be an IoT specialist; in e-commerce a delivery drone design specialist; in financial service, this might be a forensic investigator and so on. As AI adoption increases, we see that each industry will have specialised requirements. As an aspiring professional, we would encourage you to learn the basics well, and then choose 1-2 specializations to focus on.

3. Cybersecurity will come to depend heavily on AI

In the data age, information is every business’ most valuable currency. As a corollary, it is also the asset under most attack. For enterprises globally, cybersecurity is emerging as the biggest tech challenge in this decade. Recent research finds that 69% of enterprise executives believe that AI is necessary to respond to security threats. Specialists in cybersecurity — forensic analysts, ethical hackers, security architects etc. — will be in demand.

4. Artificial intelligence Trends: AI will power augmented analytics

Most businesses have solved the problem of data acquisition today. But deriving meaningful, relevant and contextual insights from big data is a challenge that most enterprises suffer. Augmented analytics aims to solve that. The augmented analysis is the technique of leveraging machine learning (ML) and natural language processing (NLP) technologies to perform analysis and draw insights without human intervention. In fact, AI will also perform data cleansing, categorization etc., accelerating insights. In the next few years, specialists who can build algorithms and systems to automate insights generation will be in high demand.

5. Graph databases will take over from relational databases.

Software for a very long time has used relational databases to store their information in the form of tables, rows and columns. This is great for structured information and specific purposes. However, for unstructured big data analytics applications, this might not be the best database design. Which is why we’re seeing a significant rise in the use of graph databases for AI applications. Graph databases are a collection of nodes containing the information and edges identifying the relationships. Gartner predicts that graph analytics and databases will grow at 100% until 2022 powering complex and adaptive data science. Careers of those in database design, management, architecture etc. will see a fundamental shift towards graph databases for AI technologies.

6. The model building will be automated

Building a machine learning model is often the first and most important step in developing AI capabilities in an organisation. But this can also be time-consuming and demanding on human resources. Tech companies are noticing this and building solutions to automate model building. For instance, Google’s CloudAutoML enables non-data scientists to build models using a graphical user interface across computer vision, NLP etc. While this is a nascent trend today, we expect this to be the artificial intelligence future, gaining popularity, given its ability to democratise artificial intelligence without the heavy investments in AI technologies or people.

7. But humans will be put back in the loop

Stories of AI being biased and discriminatory have been plenty. Enterprises have had to withdraw flagship AI solutions because they had the very biases they were built to eliminate — Amazon’s recruiting tool and Apple’s credit card are prime examples. There is a global movement calling for humans to make the final decisions with input or recommendations from AI. In fact, governments are even building frameworks to mandate human supervision for AI processes. 

8. Hardware will evolve as software does

As more data is collected and complex computation is being performed, the hardware is being forced to match up. Hardware manufacturers are constantly packing high-performance processes and graphics processing units into their hardware enabling everyone with a laptop to perform complex functions. But this is bound to reach its limit soon. Which is why we are seeing the development of specialized hardware optimized for artificial intelligence functions, like the neural network processing unit (NNPU). As the world of AI evolves, the hardware industry is going to innovate significantly — opening up jobs beyond software.

9. Edge devices will power the next generation of AI

An edge device is a device that monitors data flow at the entry point to an enterprise’s or service provider’s network. Currently, data processing happens in the backend with the edge device receiving the results. With the evolution in GPAs, AI chipsets and growth in IoT, AI technologies will run on edge devices which will enable more real-time analysis and data processing especially in places where security and privacy are crucial.

10. Multi-agent reinforcement learning will gain popularity

Multi-agent reinforcement learning (MARL) is the next level of machine learning. In fact, it’s a deep learning discipline that facilitates learning through multiple ML agents to interact with their environment. In traditional ML scenarios, where one agent interacts with the environment, changes happen only as a result of that one agent’s actions. In MARL, the environment changes as per the actions of all agents in it. 

Data scientists and deep learning specialists are using MARL to train artificial intelligence to work collectively in cooperative or competitive modes, or sometimes a combination of both. Successful MARL projects will open doors to complex AI applications in real-world scenarios — opening up another wave of opportunities and markets.

However, not all trends are equal in the world of AI. Some of the trends we see, like specializations gaining popularity or cybersecurity job market growing, are sureshot indicators of how the short and medium-term future will be. But trends in edge devices and MARL are just high-level indicators of a possible artificial intelligence future. Depending on where you are in your career, your skills, goals and what excites you, you might choose a different trend to ride. Remember, whatever trend you choose to follow, AI is here to stay. If you’re excited by the opportunities it opens up, you must consider Springboard’s 1:1 mentorship-led, project-driven online learning program in the AI/ML career track. Oh, did we mention the job guarantee? Check it out now!