Artificial Intelligence (AI) is not a new concept – it’s been around since 1956. For decades, we’ve seen the hype around machine-based learning play out in movies, such as Star Wars, The Terminator, Star Trek. But only recently have we seen AI start to transition from sci-fi to the mainstream. Today, AI is actively being used in business across all industries to predict sales and marketing outcomes, speak to customers via chatbots, or replace redundant operational tasks with intelligent automation.
Here are just some of the many use cases of AI in business:
Types of AI
At BDO Digital, we describe AI as the technology that mimics learning and problem-solving through advanced algorithms and machine learning. But what does that look like in the real world? Here are three primary types of AI in business today.
Robotics Process Automation
This is a software that can be easily programmed to do basic tasks across applications just as human workers do. For example:
- Informational – bots answering questions
- Productivity – intelligent automation for everyday work processes
- Commerce – Process orders and transactions
This is a set of services available to companies to make their applications more intelligent, engaging, and discoverable. For example:
- Smart Dashboards – visualize machine learning results with dashboard tools like Tableau or Power BI
- Natural language processing – helps computers analyze text and speech data to communicate effectively with humans
- Smart Applications and Devices – automate simple routine tasks or provide relevant data to the person or team that needs it, when they need it, with the proper context.
This type of analytics uses data to determine patterns and predict future outcomes and trends. It includes what-if scenarios and risk assessment. For example:
- Test large numbers of variables, develop and score models, and mine data for unexpected insights
- Facilitate fluid decision-making, transitioning from batch/historical analysis to real-time and even streaming based decision making
- Utilize historical data to predict a value (Business Intelligence)
Where to Begin
With an abundance of data and opportunities to leverage AI to launch your business ahead of the competition, it’s easy to see why every organization would be eager to get started. And yet our 2018 Tech Insights Survey findings show that only 19% of businesses are actively planning their analytics/big data initiatives. Even less (3%) claim to be experimenting with artificial intelligence.
The main challenge is a lack of internal expertise to help lead the charge. There are two main roles behind AI that aren’t often found in midsize organizations – data science engineers to build the infrastructure and tools needed to convert raw data into usable business insights and applied data scientists to focus on the research and advanced mathematical and statistical analysis of that generated data. Fortunately, more service providers are emerging that understand the needs of midmarket and can help cost-effectively bridge the skill gap. However, there’s more to a successful AI project than the actual development of a solution.
Before you can predict the future, you need to know your present. Our Data Analytics Accelerator can help your organization develop a data analytics strategy to drive better business outcomes. We’ll review your existing analytics needs including key users and use cases, review your current database, review potential predictive analytics uses cases, and finally deliver our findings and recommendation plans.