The epidemic has increased the use of artificial intelligence in various businesses. IDC forecasted in 2019 that investment on AI technologies would reach $97.9 billion by 2023. Since the COVID-19 epidemic, the prospective value of artificial intelligence has only increased. According to a McKinsey State of AI survey released in November 2020, nearly half of the companies have embraced AI functionalities. This post on AI trends will assist you in better understanding upcoming AI trends.
The primary goal of AI adoption is to increase the efficiency or effectiveness of processes. It can also be used to enhance stakeholder engagement. Let's have a look at the top 10 trends for 2022.
1. Greater Cloud and AI collaboration
According to Rico Burnett, AI will play a crucial role in the widespread adoption of Cloud Solutions in 2022. It will be capable of monitoring and managing cloud resources and the large amount of available data by deploying artificial intelligence.
2. AI solutions for IT
In 2022, the frequency of AI solutions being created for IT will grow. According to Capgemini's Simion, AI solutions that can identify typical IT problems on their own and self-correct any minor faults or issues will become more popular in the future years. This reduces downtime and allows teams in an enterprise to work on high-complexity projects while focusing on other things.
3. AIOps become more popular
The diversity of IT systems has grown in recent years. According to Forrester, vendors would demand platform solutions that integrate more than one monitoring discipline, like application, architecture, and connectivity. With AIOps solutions and increased data analysis, IT management and other teams may enhance their critical functions, decision making, and duties. Forrester urged IT leaders to seek out AIOps providers who will enable cross-team cooperation via end-to-end dynamic content, data linkage, and integration of the IT functions management toolchain.
4. AI will help in structuring data
We may see more unstructured data processed with NLP and ML technologies in the future. Organizations will employ these technologies to generate data that RPA (robotic process automation) technology can use to handle transactional activities within an organisation. Unstructured data can be easily turned into structured data with the power of artificial intelligence, which can deliver a defined output.
5. Artificial intelligence talent will remain tight
The availability of talent is predicted to be a barrier to the adoption of artificial intelligence in 2022. There's been a chronic talent vacuum in AI, and organisations have now recognised its potential. It is vital to bridge this gap and educate artificial intelligence to a broader range of people. In 2022, it is critical to ensure that a broader set of users has access to AI to concentrate on technology, learning methodologies, and enabling a shift in the working environment.
6. AI in the IT industry
The implementation of Ai in the IT industry has been steadily increasing. Simion, on the other hand, thinks that organisations will begin to deploy AI in production and on a huge scale. A company can obtain ROI in real-time by utilising artificial intelligence. This indicates that companies' efforts will be rewarded.
7. Augmented Processes become increasingly popular
When it comes to production and automation in 2022, artificial intelligence and data science will play a role. Data ecosystems are flexible, lean, and give data to disparate sources in real time. However, it is vital to lay the groundwork for adaptation and creativity. Companies will take a step further in improving their augmented business and innovation processes. Software development processes can be enhanced with Artificial Intelligence, and we can seek a broader collective intelligence and increased collaboration. To transition into a viable delivery model, we must build a data-driven atmosphere and move beyond the experimental stages.
8. Artificial Intelligence will become more explainable
As more data restrictions are implemented, trust in AI will become increasingly important. To effectively grasp and describe how each characteristic contributes to the machine learning model's final prediction or outcome.
9. Voice and Language Driven intelligence
The increased use of remote working, particularly in customer service centres, has created a wonderful opportunity to implement NLP or ASR (automatic speech recognition) capabilities. As per ISG's Butterfield, only about 5% of all client contacts are consistently evaluated for quality feedback. Because one-on-one coaching is unavailable, organisations can employ artificial intelligence to do routine quality control on customer knowledge and intent to assure ongoing compliance.
AI will become increasingly critical as organisations seek to automate day-to-day processes and analyse COVID-affected datasets. Since the lockdown and work from home policies were implemented, companies are more digitally connected than ever before.