An Enterprise Guide to create a successful AI Strategy

The era is of AI implementation. AI and automation have completely evolved the way we work, communicate, and live out our daily routines. Data science is no longer just about research, but the focus is now on solving problems with the right toolkit, Right from manufacturing to marketing, AI has raised productivity and streamlined business operations. 

In this modernized era, executives are also looking for AI-driven solutions to stay ahead of their competition. However, many companies who wish to adopt AI still lack the key strategy, which is essential for achieving enterprise-wide AI adoption. 


What is AI?

Artificial Intelligence, AI relates to the theory and development of software that is capable of performing tasks that usually require human intelligence, such as speech recognition, visual perception, language translation, and decision making. To put it more technically, we can call it an umbrella covering processes of machine learning, intelligent automation, cognitive computing, machine learning, and deep learning. Popular instances of AI applications include- Amazon Alexa, Siri, Google Home, Google Assistant, Apple HomePod. 


Significant Use cases of AI in enterprise and how that enterprise benefited with the same

  1. Customer Relations via Automation

Queries sent through emails or forms and then waiting for their responses is a thing of the past. Chatbots, Instant messaging platforms are some of the latest trends in the field of customer relations. AI and ML have made it easy for companies to access their customer on every platform. AI avails NLP (Natural Language Processing) techniques to interpret data and apply logical algorithms to generate useful insights. Using this, analysts will have a clear idea of the data needs and what main factors are required to be tracked. 

  1. Project Management

AI-powered Project Management solutions have been aiding in the prioritization and management of activities by diving into the impact analysis. AI solution can detect critical tasks and raise reminders for the same, whenever needed. This has brought a change in the workflow of workspace and increase employee efficiency standards. The advanced technology also aids in determining the deadlines and later generating regular reports for the management review. 

  1. Data Analytics

AI has revolutionized the data processing workflows and has delivered actionable insights for quite a period. It assists the employees by presenting them with patterns, trends, anomalies, and relationships which serve as critical decision-driving metrics. AI has shifted the organization’s concept of data from Describing to Monetizing. It does not also segregate the data into a presentable form for users but also generates an opportunity for companies to turn insights into profits. AI aids in expanding business verticals and customer bandwidth. 

  1. AI in recruitment

AI saves HR people from the tedious and monotonous process of shortlisting job candidates for further rounds. It optimizes the process of recruitment by introducing keyword-based searches. It helps in analyzing the filled application form by candidates which makes the process to be sharp and data-driven. 

READ ALSO  How to Analyze Instagram Story Performance Through Story Insights

Hiring is one thing, and retaining the employee is altogether another. AI-enabled solutions can assess the employees’ mindsets and create a plan directing their sustenance in companies. 



AI Strategy

An AI strategy is a sketch stating the way technology is set to achieve business goals. It helps in identifying the AI assets that grant the company an edge over its competitors. 

Now that we are aware of the term AI strategy, it’s time to check out the pointers that are needed to be executed for an effective strategy implementation- 


Step by Step guide to create successful AI Strategy-



  • Start aligning with your objectives


During the phase of AI transformation, most businesses make the mistake of keeping vision and execution separately. This gap results in a disjointed and complicated AI solution that can take years to amalgamate. Although, it is not so difficult to avoid such a situation by selecting AI programs based on your concrete business goals that have been designed at the project’s outset. 

It is quite essential to align your corporate strategy with measurable objectives for guiding your AI deployment. Once done, it will be easy to escalate down the enterprise-level strategy into product level strategies. 



  • Search for Stakeholders


AI projects can easily create compliance, privacy, ethical, or bias issues for companies, and hence it is vital to raise stakeholders from a wide range of companies. Companies should have compliance, risk, legal, and other such experts as a part of their strategizing process. When AI is utilized in the customer relationship process, companies need to be wary of a number of privacy pitfalls. By having security representatives from the security teams, right from the beginning can help in avoiding such risky issues. Have all the stakeholders organized around the same table, rather than getting them operated in isolated groups, can ensure the coverage of all viewpoints. 

READ ALSO  How to Analyze Instagram Story Performance Through Story Insights



  • Get a versatile AI team


Create a versatile AI team possessing members from different departments, such as Research & Development, web design, and engineering. This versatility will help in assessing how your AI strategy can best serve the individual needs and will ensure that it meets the objectives for stakeholders. 

It is not always possible to deploy the right strategy in the first go; therefore iteration is essential. By promoting a culture of experimentation, the AI team will be able to locate the appropriate assets, giving you an edge in the competitive arena. 



  • Create Customer-centric KPIs


Customer- centricity, popular talk amongst the business leaders. In the old days, many companies were following a product-centric instead of a customer-centric approach. First, the products were built, then the customers were found. But with time, everything changes.

During the creation of AI strategy, generate customer-centric KPIs that align with the overall corporate goals. It is also essential to continually evaluate the product execution back to these customer-centric KPIs. 



  • Select the right problem


This one might look like part of common knowledge, but when you look from an enterprise perspective, the problems you wish to overcome are going to have a huge impact on your business. Some problems are not even AI problems, and the ones that are, your company should advocate the delivery through mini lighthouse projects that can act as a beacon for their abilities. 

To find out the “lighthouse” projects, the enterprise will have to assess the overall objective and significance of a project. Lighthouse projects should be delivered in around nine weeks instead of nine months. These small wins will be multiplied and create the overall transformation. 

READ ALSO  How to Analyze Instagram Story Performance Through Story Insights


AI is a journey

Like any project, the sure-shot formula for successfully implementing an enterprise-wide AI strategy is- Nurture the idea, Plan, Execute, Improvise, and then Scale. Prove the lighthouse projects, upskill the AI team, and streamline the process. Foster the culture of learning and improvement with a customer-centric approach and drive a real transformation. 

Got some suggestions, feel free to comment below.

Leave a Reply

%d bloggers like this: