Artificial Intelligence Strategy, Where do I Start?

Artificial Intelligence Srategy

Artificial intelligence is here to stay, and the best way for business leaders and entrepreneurs to prepare themselves for the future is by getting ahead of AI strategy.

There are many ways that you can get a head start on your competition by implementing artificial intelligence into your company now.

In this blog post, I am going to discuss about how to develop Artificial Intelligence Strategy and where to start?

I will be sharing with you a step-by-step process on how to build an AI Strategy in your business.

Why AI and why do we need a strategy?

With the increasing demand for AI in the recent times, businesses are in a dilemma whether it is fruitful to catch up on the hype train of AI, invest in it, or is it just a bubble waiting to burst.

Business are asking question “Why is AI important?”

AI is needed now more than ever…

· For companies to gain competitive edge.

· Easy accessibility, solutions now deployable to the cloud at a fraction of the cost.

· Fear of missing out on the next wave of disruption.

· Technologies behind AI are getting less and less expensive.

· And AI is the next big thing.

Businesses can and should ensure themselves to be future proof.

If business is to capitalise on the AI opportunity, they need to have well thought out strategy.

Before getting into the strategy, let’s have a quick look at AI Basics.

So What is AI

Artificial intelligence (AI) involves using computers to do things that traditionally require human intelligence.

Machine Learning is a subset of Artificial Intelligence and is a science of getting computers to learn and act as humans do.

And

Deep learning is able to process, interpret and make use of far larger and more complex data sets.

How does the Future of AI Look

It is predicted that by 2024, AI will be integral, to every part of the business, resulting in 25% of the overall spend on AI Solutions.

What are some of the benefits AI can bring for business:

· Increased Automation

· Increased Productivity

· Smart Decision Making

· Solve Complex Problems

Here are some common Use Cases of AI in Financial Services Industry:

· AML and Fraud Detection: to predict fraud and money laundering

· Credit Risk: and Credit scoring: to determine which applicants are higher default risk

· Cyber Security: to detect anomalies in the device usage and legitimate threat

· Regulation: to automatically track, capture, and classify financial services regulations.

Now that we got the AI basics covered, lets jump into key topic.

How can we bring in AI change into the organisation and where do we start:

We start by Developing an AI Strategy.

Lets now look at the step by step process in developing AI Strategy:

Step #1: Build Awareness

One of the first things enterprises need to do is begin working towards increasing their awareness about artificial intelligence, so there is a good understanding of what AI Is.

Step #2: Generate Ideas

A great way to spark interest and generate ideas is through an ideation workshop.

Some ideas to explore are:

· High-risk customer account openings

· Flagging suspicious transactions

· Classifying articles based on content

· Identifying anomalies in data

· Keep track of regulatory changes

· Automatically flagging PII data

And the list could go on and on… but you get the gist of it… There is a huge potential for AI in every part of the business…

Step #3: Key Considerations

AI team that you need to have:

This typically includes Business decision maker, Data Analyst, Data Engineers, Machine Learning Engineer and Data Scientist required at various stages of the project.

Ethical Issues to be managed:

· Inherent bias in data will result in biased AI outcomes.

· Inability to explain the algorithms which are driving AI decision making.

· Social Impacts: company closures, job losses, new companies and jobs being created, etc and its impact needs to be worked through

Step #4: Choose a business problem

Choose a business problem suitable for a AI solution from the various ideas generated through ideation workshop.

Step #5: Select the right AI solution

· Bringing an AI-powered technology into your business could be very complex, time-consuming and expensive.

· This simply isn’t possible for every organisation. One way to address this challenge is to leverage the power of cloud-based AI services.

· For instance Amazon provides their customers with a pay-as-you-go, ready-made solutions for a variety of uses cases.

· There are out-of-the-box solutions that can be deployed in your business with some minor tweaking. eg. Amazon Comprehend.

· Then there are Platforms: for developers to quickly build, train and deploy their own functions. Eg. Amazon Sagemaker

· Choose the one that best fits your use case

Step #6: Build a proof of concept.

Some key considerations to keep in mind:

Strategic relevance:

· This is an important step in the entire process and will underpin the success of AI in your business.

· Ensure that the idea you have chosen aligns with the strategic goals, objectives and priorities of the company.

· Ensure that it gives the strategic impact you want to achieve.

Key performance indicators:

Determine what success looks like and how you will measure the success.

Commercial realities:

Is the idea commercially viable, what is the Cost and the Return on Investment.

A go-to-market strategy if your idea is a good one: how to launch the product, what training needed and any obstacles to overcome

Step #7: Last and the final step:

Create a Roadmap that shows how to develop an AI use case into production.

Based on the work you had done so far, use it to build a roadmap that covers:

· Strategy

· Capabilities

· Prototype

· Delivery & Governance

· Benefit Realisation

Conclusion

Let’s now summarize the key areas to address while developing an AI Strategy:

· What is your business strategy and purpose?

· Build an AI Vision for your business.

· What are your key strategic priorities?

· What problems/opportunity exists that needs to be addressed as part of strategic priorities

· Identify an AI use case to work on

· Key benefits AI solution provides

· Why AI over anything else? Can we address the problem or opportunity without an AI

To conclude, brining AI into your business is not a difficult process if you follow the step-by-step process that are strategically aligned to business.

Hopefully this was a useful blog.

Thanks for reading.