Artificial Intelligence (AI) and machine learning (ML) are highly advanced technologies that will transform people’s lives on a deeper level than one can imagine in the years to come. The AI and ML market has been expanding quickly for a while. A Fortune Business Insight report predicted that investment in machine learning would reach $209.91 billion by 2029.
Looking ahead to the year, if there is anything we can be certain of, it is that the businesses that are equipped to deal with uncertainty — from market fluctuations to geopolitical instability will be the ones best positioned to serve their customers, employees, and stakeholders. AI has seen exponential growth in the last five years because it has gifted humans with new capabilities to use data to swiftly respond to changing environments as soon as new data comes in.
We have listed down the major AI and ML trends that will be dominant in 2023 and beyond.
AI to boost digital immunity & resilience:
The main goal of a digital immune system and data resilience is to enhance user experience (UX) and reduce system failures that negatively impact business performance and customer experience (CX). Gartner predicts that by 2025, organizations that invest in creating digital immunity will experience an 80% drop in downtime, which will see a steep increase in CX.
As of today, 100% automation is still not attainable since it requires intensive maintenance, which calls for human involvement. Organizations may reduce the need for human intervention in software testing by using AI-augmented testing. It goes beyond basic test automation by including completely automated test planning, creation, maintenance, and analysis. The combination of test automation and artificial intelligence may work wonders for any business in such a situation.
AI to power advancements in computer vision:
AI research in the area of computer vision teaches computers to extract and decipher information from picture and video data. Computers can identify things and take action by applying machine learning (ML) models to photos, such as unlocking your smartphone when it detects your face.
According to a McKinsey report, by 2024, more than 50% of user touches will be augmented by AI-driven speech, written word, or computer-vision algorithms.
With the use of cutting-edge cameras and sensors, this AI-based technology is utilized in the healthcare industry to visualize and extract data.
An AI-enabled computer vision system, for instance, may be trained to spot tumors in an MRI image. A computer vision system may be used to analyze medical photographs and suggest the best course of action for a patient depending on their unique situation.
AI to become ethical & responsible:
AI still faces difficult legal and ethical problems. Deep fakes, biased algorithms, and models that have deteriorated over time are all alarming reminders that legal frameworks must change to keep up with the rapidly developing AI industry.
The trust would grow in the ecosystem as businesses strive to make their ML models really ‘interpretable’. This would have a favorable effect on adoption rates, ushering in a period of enhanced decision-making in which people and robots would make decisions in unison.
Date lakes & self-serve analytics to increase RoI:
Organizations need to connect data lakes and warehouses to create a data lakehouse that delivers greater speed, storage, and operational savings in order to receive a higher return on investment on these investments.
When self-serve analytics tools are implemented on top of a data lakehouse, real-time insights may be obtained. Redesigning the data architecture is necessary for this endeavor, which is an operational task. Companies in the pharmaceutical, automotive, and consumer sectors that handle a lot of data stand to gain from operationalizing their data lakes.
Generative AI to be a game changer:
2023 will be a turning point for the generative AI industry. In the second half of 2022, the world started to realize the benefits and potential of generative AI developments as well as their limitations.
The market is expected to reach $422.37 billion by 2028, with global AI investment increasing from $12.75 million in 2015 to $93.5 billion in 2021, according to The Financial Times.
ML algorithms known as “generative AI” are capable of extracting new meaning from text, pictures, code, and other types of material. DeepMind’s Alpha Code (GoogleLab), OpenAI’s ChatGPT, GPT-3.5, and DALL-E, which are powerful language models and picture generators, are the leading generative AI tools right now.
We are gradually moving into a new phase in the development of the AI sector as generative AI develops further. According to Gartner, generative AI models will be responsible for at least 30% of all novel medicines and materials found by 2025.
Concluding lines:
AI has evolved from being merely fascinating to having a significant influence on both organizations and consumers. AI usage will soar in 2023 thanks to the quick spread of models across all sorts of applications. AI will make standard software and equipment that businesses use every day smarter, while new-age apps will proliferate and continue to straddle the line between reality and science fiction.
Disclaimer
Views expressed above are the author’s own.
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