Expect more AI deployments in the coming year, thanks to technology advancements and user understanding.
While Artificial Intelligence (AI) was a popular subject this year, actual AI deployment in enterprises remains in its early stages. However, 2018 did see a significant "table setting" for AI advancements in 2019.
In 2018, AI applications like predictive analytics, diagnostic analytics, automation, and natural language/machine learning expanded. Everyday business users began to see the benefits of AI in their personal smartphones and appliances—and how these advantages could translate to business in virtually every industry sector.
SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research)
Going forward, 2018's lessons and experiences will forge a bridge into more widespread adoption and acceptance of AI in the new year.
Here are six examples of how AI has paved the way for more enterprise adoption in 2019:
1. The democratization of AI
Much like cloud computing in its early days, business users and IT initially scratched their heads around the abstract concept of AI. In the case of cloud, once iPhone owners began storing information in the cloud instead of on their devices it began to define what cloud computing could mean for business. In a similar fashion, AI comes alive as a practical everyday concept for many people as they use AI like Siri and Alexa.
This rudimentary understanding of AI engages individuals with AI's basics—and will help drive more AI adoption in business in 2019 because some comfort level already exists.
2. IT automation
IT automation will continue to be one of the most active areas of AI deployment in 2019 as it was in 2018.
According to a Harvard Business Review research study, 44% of companies in Harvard's worldwide study said they were using AI to detect and to deter security intrusions, while 41% said they were using AI to resolve user technology problems. Another 34% said that IT was using AI to reduce production management through automation, as well as to assess internal compliance.
SEE: Artificial intelligence: Trends, obstacles, and potential wins (Tech Pro Research)
3. Hybrid business processes
The healthcare sector utilized AI and analytics tools like IBM Watson to develop and confirm medical diagnoses. We also saw the use of hybrid man-machines with self-driving trucks, where drivers let the trucks and their AI systems drive vehicles on open highways, but then took over the controls to navigate through congested cities.
Look for hybrid man-machine business processes that were used in 2018 to pave the way for more hybrid business processes in 2019.
4. Growing AI talent
If anything, 2018 unearthed a lack of awareness and appreciation that companies had for their own internal business talent. The fact that AI was primarily deployed in IT and not in other business operations demonstrates this.
2018's lesson for 2019 is to recognize high knowledge individuals in different areas of the business. You will need them to train the machines and software if you hope to incorporate more AI in everyday business operations.
5. The emergence of natural language and speech recognition technologies
Sound has lagged visuals in the AI world, but 2018 saw a flurry of activity in sound-to-text and in voice response systems and mobile apps. This activity ranged from verbal commands to robots in warehouses and to the simple use of Alexa in small office settings.
Look for natural language and voice command applications to grow in 2019.
SEE: Quick glossary: Artificial intelligence (Tech Pro Research)
6. Machine learning technology
In 2018, machine learning (ML) applications expanded. ML uses software algorithms that enable computers and robots to learn from their experiences so that they can become better at predicting and doing things.
A prime example of ML in 2018 was its increased use in predicting when components on equipment and sensors were likely to fail so that maintenance could be done proactively, thereby avoiding downtime. 2018 also saw major companies like Amazon, Google, and Microsoft sell ML platforms in the commercial market.
Look for more industry sectors to incorporate ML in 2019.
- Google DeepMind founder Demis Hassabis: Three truths about AI (TechRepublic)
- Cheat Sheet: Artificial intelligence (TechRepublic)
- 6 AI priorities your business can't afford to ignore (TechRepublic)
- 7 enterprise technology trends that will drive digital transformation in 2019 (TechRepublic)
- Google, Amazon, Microsoft: How do their free machine-learning courses compare?
- Mind the gap: AI and machine learning lag in adoption (ZDNet)
- How machine learning and AI are transforming customer support (ZDNet)