If you do not learn how to use and tame artificial intelligence, it has the capability of creating havoc in your organization.

In this article we have discussed about AI and key challenges, how it provides business value, how to scale artificial intelligence, one big picture AI strategy and what you should do. Insights are based as per the keynote by Dr. Raj Ramesh’s on Future of business with AI, at the 5th Annual CULytics Virtual Summit, 2020.

1. What is Artificial Intelligence?

   Artificial Intelligence is a mechanism that introduces cognitive ability in machines so that they can act like humans, and behave like them. Machine Learning is a subset of artificial intelligence.

   The AI stack starts with infrastructure, data to be used, machine learning, followed by application, processes, insights, and decisions. Artificial Intelligence prepares you for rapid actions and adds value to the business.

2. Business Ecosystem and AI.

   If you are not part of Data exchanges within the ecosystem, you will be left behind.

   On the business side, if a credit union wishes to grow it can do so through a particular market segment like insurance, or home loans, etc. The channel through which you choose to do this is important. You have to collect information about customers. Data needs to be used with cognition. Initially, it can be from third party sources. The data sharing can diminish the value of your data if it happens outside your organization.

   On the technology side, if you put all technologies together, it will create uniqueness. It matters more how you put technologies together.

   AI also involves many role changes, but it will only get better. For employees, you have to create an environment for transformation.

3. Scaling Artificial Intelligence

   In the absence of Scaled AI, you will only have a bunch of in silos implementations that will not work. The question you should be asking to be able to scale AI, is ‘what business capabilities do you want to explore and are willing to focus on?’ There are so many places to introduce AI, from Backend to chat-bot, but you should first prioritize. The human-machine collaboration gap should be reduced.

   AI relies on the consumption of good and meaningful data, which is consolidated, protected, and governed.

4. Leadership support, money, skills, resources, employee understanding are some real constraints that need to be looked at. A culture that is adaptable to change should be built within the organization.

5. AI Framework and strategy

   While thinking about your AI framework and strategy there are multiple things you should keep in mind like do you want to build an in-house platform or are you going to outsource it? Are you going to use open-source tools or develop tools inside or use vendors? Are you going to use a high-value process or least risk process?

   What capabilities will you look at and how will your organization structure be designed? These decisions cumulatively constitute your AI strategy. AI framework comprises of all the choices you can make, and your AI strategy is the choices you make.

6. AI Application
   • You could use AI in customer-facing operations such as using predictive analytics, robot advisors, or chatbots.
   • AI could be used in customer support roles, for example, credit scoring, wealth management, etc. This enables the customer experience.
   • AI could also be used in your back end systems such as for governance, compliance, intelligent document processing, physical security, asset management, fraud detection, etc.
   • What happens outside your organization, your business ecosystem should also be taken into consideration.
7. Next Steps
   • Look at the customer- Emphasize on introducing innovative products, and the right segments of members.
   • Look out for opportunities for collaboration with partners
   • Look inside the organization – Build the talent and develop an environment where employees can grow.

CONCLUSION

AI has a lot of power and is beginning to form a crucial part of digital transformation. You should just know how to manage it and tame it. In your organization, develop people skills, because no machine can compete with that. Emphasize on learning and innovation. Collaboration is the key and makes the most of your capabilities.