Welcome everyone to 2022! I wanted to start the year with my predictions for this new year in the AI space. I know making predictions is not easy and the goal of this post is not to predict how AI will take over the world but more about how AI will become more applicable to everyone.
Low Code and No-Code
2021 was a huge year for No-code AI and 2022 I predict will be even bigger. We will see huge improvements in the tools available that will enable new complex use cases for non-technical experts. We are seeing the democratization of AI at all levels.
- Pre-trained APIs and Language models such as new versions of GPT-3 will be more accurate and customizable.
- No-code AI tools will cover the entire end-to-end AI lifecycle with very intuitive and flexible user interfaces. ML components will be easy to re-use, and capabilities like Feature Stores will become more mainstream.
- Enterprise requirements will be met for security, scalability audit, monitoring, and deployment options.
This 2022 we will see more capital invested in No-code AI startups and big tech companies such as AWS, Google, IBM, and Microsoft will continue to improve their No-code AI solutions.
Businesses will continue to face increased pressure to rapidly build and deploy new capabilities and drive ROI to stay ahead of the competition. Digital Transformation and Automation will accelerate thanks to these tools, and more enterprises will benefit from adopting an AI-first approach. No-code AI will grow its footprint and we will see new challenges of No-code solutions sharing environments with traditional software environments in the enterprise. Trust in No-code solutions will grow and technical users will start adopting them, and not just business users, and that will unlock new forms of collaboration.
The high cost of labor and skills shortage will make Low Code and No-code AI a no-brainer for 2022!
MLOps and Responsible AI
There is a lot of talk about AI not going into production enough and companies spending a lot of money on prototyping and experimentation. This 2022 we will see a big transition here. Part of the lack of adoption is trust in AI, and MLOps and Responsible AI is now a capability ready for Prime Time in most of the AI solutions in the market. This wasn’t the case a few years ago, but right now companies will be able to easily deploy models into production using their favorite method and track the model performance, explainability, bias, drift, and automatically retrain all while providing full transparency on the predictions that AI is doing on new data.
No AI project will go into production without the capability of trusting it. There is more awareness about the need for responsible AI and perhaps we will even see new regulations that will enforce this for specific use cases such as for AI screening resumes for hiring decisions. Some companies are already partnering in the Data & Trust Alliance, a cross-industry consortium to “detect and combat algorithmic bias”.
In 2022, AI practitioners will build responsible AI practices in their day-to-day workflows.
Get ready for 2022!
This 2022, this community will be really active in providing education, and news and bringing everyone in the No-code AI space together. The goal is to make AI practical and this year we will have more options than ever for that. This will be the year of No-code AI maturity and it will play a major role in the innovation strategy for enterprises across all verticals. Measuring the Business Impact of AI solutions will also become mandatory!
I wish you all a happy and healthy 2022!