A full-fledged artificial intelligence would arguably be humanity’s greatest invention.
AI’s power for transformation is believed to be extraordinarily high. So high that Sundar Pichai has claimed that its invention would be more impactful than the invention of fire or electricity.
A full-fledged AI is perhaps two or four decades away. But that does not mean AI today is nascent. Artificial intelligence and machine learning, its predecessor, are technologies growing at a tremendous pace. Every few months, a breakthrough is said to disrupt the industry. Thanks to the rapid growth in processing speeds, ML and AI, software, robust internet and cloud infrastructure, and access to ever-increasing data, the industry is far from nascent.
And that is true for both growth and adoption. Already, an overwhelming majority of Fortune 500 companies use some form of AI to improve their bottom line. Almost 99% of the companies use AI to automate hiring, most to find and screen candidates, while a few even to interview them. Others automate payment processing, content creation, and warehouse operations. And as AI becomes scalable and cheaper, even mid-sized and small companies plan to incorporate AI in their workflow.
Long story short, there is so much to look forward to, as companies use AI to solve a great variety of problems. Not just the big ones like climate change, space exploration, and drug synthesis. But also, smaller ones, such as image searching and web design. Here is what we expect 2022 to have in store for us.
1. AI-augmented, hyper-automation
What is intelligence? Intelligence can be defined as the ability to emulate human thoughts and actions. Intelligence in technology is not absolute, but a spectrum. On that spectrum, simple automation technologies like Robotic Process Automation (RPA) lie on one extreme. In contrast, strong AI lies on the other.
AI in 2022 will be far from strong. But it is slowly getting there. We have already seen AI emulate human actions, albeit simple ones, like compiling and updating reports or visualizing data. However, in 2022, AI will step up. It will automate a more complex range of human actions, and even human thoughts to a small extent (see below).
In other words, advancements will render current artificial intelligence more intelligent. For businesses, the breakthrough will redefine process automation and optimization. In 2015, businesses in the US alone employed over 450,000 bots to automate simple and repetitive operations. In 2022, the figure is expected to surpass 600,000. McKinsey estimates that for industries like manufacturing, over 50% of work could be automated.
But while automating physical work reduces cost and is always welcome, the real deal would be automating knowledge work: automated response systems, supply chain optimization, creating art, writing code—practices that demand the use of knowledge, not strength and mobility.
Such an AI understands business processes more deeply. Besides automating them, it will also evaluate them, discover inconsistencies, predict them, and resolve and optimize them. That is why over 80% of executives (World Economic Forum) are accelerating their efforts to adopt AI—across technology, banking, retail, healthcare, fintech, agriculture, and any industry you could think of.
Businesses now do not just wish to automate, but to understand their processes and leverage data-driven insights generated by AI to maximize ROI and success.
2. Natural Language Processing (NLP)
Using technology is hard. Especially for the old. Only if a device would do what you told it to do?
Even ten years ago, computers were effectively incapable of understanding spoken language. And that was the case for English—languages in the minority were out of the question.
The thing is, human beings were never meant to write language, only speak it. Which is why learning to read and write English, or any other language for that matter, is much harder than learning to speak it.
But the goal of technology is to make our lives easy, not hard. And AI in 2022 will achieve precisely that. With ever-powerful, dedicated processors for processing language, NLP will take off. But we are not just making strides in hardware. With raw data available anywhere you turn, training an AI model for understanding language has become much easier.
Recently, OpenAI released Generative Pre-Trained Transformer, or GPT-3, the world’s most advanced and most expansive language model. Models like GPT-3, which uses over 175 billion parameters or rules to process language, can lead to natural-sounding, conversational chatbots that solve customer problems without pressing 0s and 1s or waiting. Think about coding without coding—just declaring a statement, while the AI transforms it into code on its own.
In fact, OpenAI is now planning to release GPT-4, a tremendous upgrade to its predecessor, with reportedly over 100 trillion parameters! Soon, we could have an AI that produces language indistinguishable from ours. Sooner than expected, perhaps.
3. Cybersecurity
Cybersecurity is a massive threat. So much so that the World Economic Forum rates it higher than terrorism.
Last year alone, over 9 billion data records were compromised. And given the increasing sophistication of cyberattacks, that number could double or triple within the next ten years. But given the increasing sophistication of AI, the number could also halve.
It has to. As we share and store more private and sensitive information online, security and privacy are no longer initiatives, but imperatives. Breakthroughs in AI could lead to stronger encryption and more advanced protection. But the very breakthroughs could help hackers reverse engineer encryption and undo protections.
Therefore, corporations and hackers are engaged in an arms race, investing and innovating to ensure they are a step ahead. In 2015, the cybersecurity market was worth over $17 billion. Today, the market’s worth is well over $60 billion. In 2026, it is estimated that of the total, over $40 billion will be invested in ML- and AI-enhanced cybersecurity.
In 2022, this sector is one to watch out for.
4. Risk analysis
Perhaps the biggest impact AI will have in 2022 would be on the data analytics industry.
The biggest advantage of using AI is that it enables companies to process both traditional and non-traditional data. Also known as alternative data, non-traditional data is unstructured and hence more challenging to quantify and process. But it is extremely valuable for its insights.
Foursquare, a location-data platform, predicted a drop in Chipotle’s sales by looking at its check-in data. Chipotle’s sales did indeed decline in 2019, but is that really a surprise? The value of non-traditional or alternative data has been known for well over a decade. First, it was the news, and now, it is social media. Twitter and other social media are critical sources of insights for fintech companies. Today, analysis to assess market sentiment is incomplete without processing their feeds.
Now it becomes clear why AI’s impact on data analytics is considered the most significant: data analytics permeates industries left and right. Besides finance, healthcare companies, too, can use AI to make more accurate diagnoses. The healthcare industry is often criticized for its reluctance to embrace digital transformation. However, the boom in wearables is bringing a revolution in healthcare. Much like determining one’s credit score, AI in healthcare will combine digital health records (traditional data) with genetic and biometric data (alternative data) to predict and prevent illnesses with greater accuracy and effectiveness.
It, indeed, is already happening. The University of Maryland Medical System developed a machine learning algorithm that analyzes patient data across 382 variables to predict the likelihood of re-admissions. Alina Health and Ascension Health developed a similar algorithm. They offered high-risk patients prevention guidance, reducing re-admissions by nearly 10%.
AI-augmented risk analysis will only get better as the internet’s reach becomes wider, devices connected to it (IoT-enabled) increase, and AI grows more advanced. Today, the world generates over 80 trillion gigabytes of data every year. Soon, the number may increase multiple-fold. Instead of merely storing it, like money in a vault, AI will ensure that we put it to good use. Invest.
After all, it is the capital for the data economy.
5. Real-time insights
The modern approach to taking business-critical decisions is not taking them in intervals, but often in real-time. Therefore, data analytics must also be carried out in real-time.
The principle of investing in real-time data analytics is simple: to make interactions or experiences—whether on a website, app, or any platform for that matter—as personalized and streamlined as possible.
For example, all businesses want is to offer their customers communication or an experience that is ideal for them at every step of their long and winding customer journey. It could be just the advertisement they are expecting. Continuous insights, therefore, are precisely the insights for which businesses must strive.
And getting them will get easier in 2022.
Modern businesses are now spending more than ever on advanced predictive analytics techniques like machine learning and AI to translate interactive data into actionable insights, in near-real-time. The result is constantly evolving prediction algorithms and the opportunity to offer more captivating, more personalized content.
Climate change is real and perhaps the biggest threat to our existence. Recent extreme weather phenomena like floods and heat waves have resulted in thousands of deaths. And if we fail to contain the rise in global temperature below 2° C (above pre-industrial levels), extreme weather events will only become more intense. Soon, life on earth, especially for poorer countries, will become uninhabitable.
Reducing our carbon footprint is not as simple as reducing the emission of carbon dioxide. Let us not forget that carbon dioxide, in fact, is not the only greenhouse gas. Climate change is an extraordinarily complex problem, and solving it will take extraordinary measures. Here is one measure: using AI.
AI can help accelerate our efforts to achieve sustainability. Take Google, for example. Google has used AI to identify breakthroughs in material design to create more efficient solar panels. It has also used its power for prediction to optimize its data centers. Today, its centers produce one-third of the heat they produced five years ago, while consuming the same amount of energy. Tesla, too, like General Motors, Apple, and a host of other manufacturers, uses AI to identify better materials and designs for its products, and to optimize its supply chain.
But sustainability is not just about fighting the climate crisis. It is also about fighting the socio-economic and cultural crises: maintaining diversity, equality, and inclusion (DE&I). Let us not forget privacy and transparency.
As explained, most companies will eventually use AI to hire. However, hire-tech companies like HireVue have been accused of using biased data in their assessment, causing their clients to, inadvertently, promote discrimination. But just like hackers can use AI to undo AI-based data protection, companies can use ethical AI to find inconsistencies and de-bias unethical AI.
With offices in New York, Austin, Seattle, London, Zurich, Pune, and Hyderabad, SG Analytics is a leading research and analytics company that provides tailor-made insights to enterprises worldwide. If you are looking to make critical data-driven decisions, decisions that enable accelerated growth and breakthrough performance,contact us today.
