Artificial Intelligence As a Part of Business Strategy

-AI which is artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. The era has been shifting towards the phase of AI which also enables its existence in business operations and strategy.

Businesses has been using AI to simplify its daily routine works which also reduces their human resource requirements. But it does not means to completely getting dependent on AI.

Building business strategies with AI means is to combine the efforts of AI and human resource of the organization for better efficiency.

Artificial intelligence (AI) has the potential to transform every business – in the same way (and possibly more) as the internet has utterly transformed the way we do business. From smarter products and services to better business decisions and optimized (or even automated) business processes, AI has the power to change almost everything. Those businesses that don’t capitalize on the transformative power of AI risk being left behind.

So what should you include in your AI strategy? When I work with a company to develop their AI strategy, we look at the following areas:

1.????Strategic AI priorities

Now that you’re absolutely clear on where your business is headed, you can begin to identify how AI can help you get there.

Examples of AI priorities or use cases include:

·????????Developing smarter products and services

·????????Making business processes and functions (such as accounts, sales and HR) more intelligent

·????????Automating repetitive or mundane tasks to free people up for more value-adding activities

·????????Automating manufacturing processes

2.???Short-term AI adoption priorities

Transforming products, services or processes is never going to be an overnight task. It may take some time to deliver the use cases you’ve identified. For that reason, I find it helps to also identify a few (as in, no more than three) AI quick wins – short-term AI priorities that will help you demonstrate value and gain buy-in for bigger AI projects.

3.???Data strategy

AI needs data to work. Lots and lots of data. Therefore, you need to review your data strategy in relation to each AI use case and pinpoint the key data issues.

4.??Change management issues

Because people are so wary of AI, particularly what it might mean for their jobs, change management is a really important part of any AI project.

Example questions include:

·????????Which employees and teams will be impacted by this AI project?

·????????How can we communicate effectively with those people about the change?

·????????How should the change process be managed?

·????????How will AI change our company culture, and how will we manage that culture change?

5.???Skills and capacity

For those companies who aren’t Facebook or Google, accessing AI skills can be a real challenge. Therefore, this step is about reviewing your in-house AI skills and capabilities, and working out where you need a skills injection.

For example:

·????????Where are our skills gaps?

·????????To fill those gaps, do we need to hire new talent, train existing staff, work with an external AI provider or acquire a new business?

·????????Do we have awareness and buy-in for AI from leadership and at other levels in the business?

·????????What can we do to raise awareness and promote buy-in?

6.??Implementation

Here you need to think about how you’ll turn your AI strategy into reality.

This might surface questions such as:

·????????How will we deliver our AI projects?

·????????What are the key next steps?

·????????Who is responsible for delivering each action?

·????????Which actions or projects will need to be outsourced?