AI and Business: The Ministry of Future
November 06, 2023: I wrote this piece in early 2018 which was before generative AI took the world by storm. As I read this today, I reflect on how pertinent the topic is even today.
Artificial Intelligence is here and it’s time for you to use it — now! In this article, I discuss AI various use cases for your business with examples from the industry and a clear roadmap to incorporate AI into your business.
There are three main types business needs that AI has the ability to support: automating business processes, gaining insights through data analysis, and engaging with customers and employees.
1. Process Automation
LorProcess automation is the interpretation and manipulation of data for existing applications by a computer software or a bot. It is the most common application of AI in a business.
- Use cases for these tasks include:
- Transferring data from email and call systems into a system of records
- Reaching into several systems to update records
- Extracting information from multiple document types and finding inconsistencies
- Reading legal and contractual documents
NASA has implemented robotic process automation in its accounts payable and receivable, IT, and human resources. Through this implementation, 86% of transactions were compiled without any human interaction.
2. Cognitive Insights
The second most common type of project uses algorithms to detect patterns in vast volumes of data and interpret meaning from them.
These algorithms are being used to:
- Predict customer behavior
- Identify credit card fraud
- Identify quality problems in automobiles
- Automate personalized advertisements
- More accurate and detailed actuarial modeling in insurance
GE utilized this technology to integrate data from suppliers that saved them $80 million in just its first year by eliminating redundancies.
3. Cognitive Engagement
The third type, cognitive engagement, includes projects that engage employees and customers with the help of chatbots and machine learning utilizing natural language processing (NLP).
Some examples of these are:
- Virtual agents that provide 24/7 customer service
- Product recommendation systems for more personalized sales
- Internal sites for employees to get answers to their queries
SEB bank, in Sweden, is using an intelligent agent, Amelia, to serve as an employee for IT support. Amelia provides IT helpdesk services to over 15,000 employees virtually and SEB will deploy Amelia externally to enhance services for the bank’s 1 million customers by the end of the year.
How should you go about implementing AI in your business?
1. Understand the technologies available to you and start using them immediately
The objective of testing different technologies is to determine which one will work best with your business, and how to utilize them efficiently. There are several steps to understand these technologies fully:
- Identify the areas of your business that could benefit most from AI technology. Often, the knowledge exists but is not properly distributed. In healthcare, for example, knowledge tends to stay within each department and practice and doesn’t flow freely from one to another.
- Next, you need to examine if the AI technologies being considered actually perform the tasks that are required. It is easy to implement these technologies, but they can lead to inefficiencies.
- Ensure that you maintain interoperability amongst the different technologies and between your employees and the technology.
- It is wiser to take small steps rather than giant leaps when assessing technology for your company.
2. Create a small team and start piloting programs
Who will test the technologies? Form a team small team that will pilot programs for cognitive applications before rolling them out across the company. You can call the team — “Department of Cognitive Applications” or “Ministry of Future”
Don’t get intimidated by your competition. Just because your competition has launched something new does not mean that you also have to jump into a project. Instead, tell your “Ministry of Future”. This will allow your team to learn from your competition and build something much better. Allow your team to build the technical skills while also moving small pilots into broader applications throughout the company.
Pfizer has more than 60 projects across the company employing cognitive applications; many of these are pilots and some are now in full production.
3. Have a plan to scale up projects in the future
Have a budget and a rollout plan ready as soon as you develop a promising product.
Scaling up almost always requires integration with existing systems. This integration is usually the greatest challenge. Having a plan in place you will make you future ready.
The health insurer, Anthem, is developing cognitive technologies as a part of modernizing their existing systems. This is a holistic approach that maximizes the value being generated while reducing overall costs of development.
Claim your Future
If you are adopting AI for now and have a plan in place for implementation in the future, you are on the best track to position yourselves as leaders in Industry 4.0. With the right planning and development, you will reach a point of maximum productivity and work satisfaction. Good luck with your “Ministry of Future”