Investing in the right AI initiatives focused on delivering specific efficiency gains in internal processes will likely propel businesses forward today and beyond.
Companies are investing in AI and machine learning models to compete in the market. Those that are putting significant investments in AI and focusing on the right use cases are reaping the benefits and leading their industry.
Our latest State of AI and Machine Learning report surveyed 501 business leaders and technical practitioners from various industries to help understand the current AI industry trends. While the report covers various topics, here are the five key reasons AI will continue to be vital for businesses’ success:
1) Increasing AI budgets show a maturing of the industry
The biggest indicator that the AI industry is growing is with an increase in budgets. This year, companies are reporting higher budgets, with 53% reporting budgets between $5K and $5M compared to just the 34% from 2020. With companies going all-in on AI, it’s proving to be critical to business success. Market leadership perception is also tied directly to budget as companies with budgets less than $500K are less likely to describe themselves as a market leader. As companies vie for the top leadership position, they will need to continue investing in their AI strategy.
2) The pandemic brought on more technology-focused strategies
COVID-19 brought a lot of changes to the industry, many for the better. 55% of respondents stated the pandemic accelerated their AI strategy as they move to more remote and virtual interactions. Companies are putting an emphasis on technology-first strategies to meet the needs of their employees and customers. We will continue to see companies allocating resources to improve their technology strategies.
3) Leaders are becoming data-centric using AI
Artificial intelligence models are not a set-it and forget-it system. They require continuous training and monitoring to be successful. Leaders are recognizing the importance as 57% of organizations reported updating their models at least monthly. This transition shows the significance of data and how essential training data is to building a successful model.
4) Delivering excellent customer experience continues to be key
Customer experiences will continue to be a driving force behind automation and AI models. Improvement in interactions with purchasing and support has become a top focus for many companies who look to improve their processes. 54% of organizations surveyed stated one of their top three use cases for AI was improving productivity and efficiency of internal business processes. It was the second most used among large organizations suggesting the importance of focusing within the organization to improve experiences.
5) Address data privacy and security concerns
Data privacy and security are a top concern for organizations as they dive deeper into data management. Many organizations are turning to external data providers to help with model training, and of those, 91% rate their organization good or excellent with addressing privacy and security concerns related to AI. According to a recent study by Stanford HAI, over 60% of organizations consider cybersecurity the top risk they are concerned about.
Research and customer and partner conversations point to the fact that organizations need to continue to accelerate their strategies to be competitive in their industries. Investing in the right AI initiatives focused on delivering specific efficiency gains in internal processes will likely propel businesses forward today and beyond.
