A Guide To AI First Strategy: A Key To Your Business Success

Are you thinking of a practical approach for your digital business transformation? Discover how successful businesses use AI First Strategy.

What Is The AI First Strategy?

Ai First Strategy is one where a business or organization’s main processes are driven by AI. It includes building an organization whose decisions are data-driven. Letting AI and machine intelligence strongly influence an organization’s decisions is beneficial because of the infallibility of machines.

By creating an AI First business model, the probability of human error is greatly reduced. That is why it is highly encouraged for businesses that aim to advance into the modern era to equip themselves with an AI First Strategy.

Disciplines such as Machine Learning, Data Science, etc. become the backbone of business processes. Though these systems will be built and maintained by humans, the results and insights that they produce will be completely machine generated.

AI First As A Mindset

It takes a lot to transform a business into an AI-first mindset. The AI-first strategy is not just a prescription of how to do things. Rather, it is a total overhaul of an organization’s culture, mindset, and goals. It requires a change on the most granular level.

This approach is so powerful and effective that it can readily be observed in how Google as a company has evolved. Sundar Pichai states in his 2017 keynote that Google originated from a mobile-first strategy. When it became abundantly clear that people are now moving on from their fixation on comfort and convenience to their fixation on efficiency and accuracy, they made the move to AI-first.

Because of AI-first, Google was able to enable conversational and sensory experiences (Google assistant), seamless usage of multiple devices, thoughtful usage of contextual information, and systems that learn and adapt. These things would not have been possible if Google stuck to a mobile-first strategy.

How AI First Transforms Businesses?

1. Eliminating Human Error through Hyper Automation

The remarkability in this approach is that human error is almost completely removed from the equation. When an organization relies on the state-of-the-art models, the biases and emotionality inherent in human decision-making is eliminated. The advantage here is that when human error is minimized, the results are better and the processes are more efficient. This results in a transformative user experience--one that taps into the psyche of the user.

Nowadays, a trend called “hyper automation” means that anything that can be automated should be automated--including legacy business processes. Thereby eliminating the possibility of human error. One example of an essential business process being subject to automation is that of cybersecurity. By 2021, AI-driven cybersecurity will be the standard.

Another example is that of IoT. AI First companies who aim to provide holistic user experiences will inevitably have to marry the AI/ML and IoT. IoT provides an avenue to provide a seamless user experience whereas AI/ML will augment that experience.

2. Ethics In AI

Of course, as AI changes the way humans live, AI First companies will have to deal with the inevitable flurry of ethical questions that are sure to come their way. Matters such as data privacy will be the subject of heated debate both in casual conversation and in congress. It is up to the organization as to how they define the moral usage of AI and how they would assure their customers.

Getting Started In AI First

1. Equip Your Organization With Fullstack AI

To enable AI First in your organization, the first order of business is to implement Fullstack AI. Equip your people with the right skills. There are many partner program offerings out there from the 3 giant cloud platforms that offer extensive training to an organization’s personnel. Bring in experts who specialize in Data Engineering, Data Science, and Data Analytics who will act as both as your internal consultants and tech mentors.

Once that is done, it is time to decide on a core infrastructure. Will you be going with an on-prem system? Perhaps you can tap into housing your resources on AWS, GCP, or Azure? Of course, if you want to develop a hybrid cloud system that is entirely plausible too. However, for purposes of starting, it is advisable to start with purely on-prem systems or cloud systems.

2. Reconcile The Tech Side And The Business Side Of Your Organization

Next, you have to define how the leap into AI First will define your organization’s projected business outcomes. This is where you will need to overhaul your business model so as to make the business side of the organization compatible with the tech side. This will warrant discussions with your existing stakeholders and as such, you have to be prepared to present a convincing argument as to why your organization should completely restructure itself to be AI First.

3. Reorganize Your Company To Be More Monolithic And Less Tribal

A traditional company is separated into departments whose processes are meant to be independent of each other. With AI First, the whole point is let AI drive the processes of the organization and as such should allow for bilateral operation between units. With a tribal structure, units are not encouraged to work in tandem with each other and instead foster a culture of competition.

Remember that AI First is also a mentality. Your people should be looking forward and thinking of ways to achieve milestones together instead of acting independently. The tribal mentality hampers growth and defeats the purpose of using AI to revolutionize internal and external business processes.

4. Centralize Your Data

You most likely have an existing database of your clients and their needs. Effort must be put into building a company “data center” where data is readily available for relevant parties to analyze. All of your projects from now on will be AI-driven and thus data-driven. Take care of your data because the quality of your models depend on it.

5. Identify Use Cases

Many of your projects will now start off as research. Thus, it is imperative to assign a group of experts to identify common client pain points and come up with use cases based on that. Remember that your models ultimately have to solve human problems. So the premise of most of your POCs will be defined on some human problem that needs to be solved by machine learning.

Get Expert Help In Implementing The AI First Strategy

Here at, our business and technology experts are passionate about promoting the AI First Strategy. As an organization that practices the strategy, we are an ideal partner in helping usher in the AI First Strategy in your company. We have experts in ML ops, cloud engineering, AWS, Microsoft Azure, and many more who will help lead the transformation of your business from traditional to modern. We will make the transformation process possible no matter how stuck in tradition your organization might be.

If you are interested in reorganizing your company to harness the power of AI-driven processes, contact us today at !

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