How to strategize AI in business

Rupal Shirpurkar
By Rupal Shirpurkar
  August 20, 2022  / 
  365     0

AI is becoming an essential part of an organization’s growth. 54% of executives believe AI has increased the productivity of the entire organization. Artificial Intelligence investigates and documents how AI is causing changes in the workforce, data management, privacy, cross-entity collaboration, and new ethical issues for business. It examines contemporary dangers and concerns related to dependency, job loss, and security. Additionally, it aims to assist managers in comprehending and seizing the enormous opportunity presented by the fusion of human and machine intelligence.


Strategizing the implementation of AI is a critical step of AI deployment to get faster ROI (Return on Investment) in minimum TCO (Total Cost of Ownership). Deploying AI without strategizing in advance gives you three-fold ROI while Deploying AI with advanced strategies can offer a 5-time return on investment.
The integration of AI with the current business workflow can be overwhelming. Often organization leaders misinterpret the working model of AI and hence cannot get the desired outcomes out of the investment.

Here are a few things to consider while strategizing AI adoption in your organization

Prioritize the domains – Prioritizing domains in which AI should be deployed first can provide a better insight into future investments. The domains which directly benefit the customers or end-users should be prioritized.

The domains with effective organizational goals, optimized cost, and improved agility provide faster ROI than others.

Center of Excellence – Center of excellence plays a vital role in the success of any deployment. A dedicated team to deal with AI will help in seamless deployment and faster ROI. CEOs have the ability to integrate AI at scale and drive returns based on organizations’ goal strategies.
Transform Work Culture – A successful deployment of AI is not possible without a shift in work culture. Employees have a habit of using legacy ways to operate in certain areas and the deployment of AI can make them uncomfortable. AI-driven culture is a crucial component of Ai deployment to leverage the benefits of AI.AI has unlimited potential to grow business and transform workflow. With a mature AI and accurate strategy, it is vital to align AI strategies with your business strategies. Deploying a new way of work without integrating it with the business goals will not generate the desired output. Your AI model should align with your business model to generate ROI.


Deploying AI cannot be an overnight task. Setting short-term goals and timely evaluations help analyze the strategies better. Another domain that impacts the successful deployment of AI is the data of the organization. Creating a data culture is an essential step with data collection and data accessibility. Having cloud support that provides real-time data to analyze the process and work accordingly is a huge part of implementing AI. The algorithms of machine learning work on big data and hence providing live data to define algorithms for the machine learning process is necessary. Having a cloud platform that works for your industry and organization goals is important for the successful deployment of AI. The data provided to any ML-based infrastructure should be seamless and accurate without any downtime. Machine Learning is a subset of AI that helps Machines or AI models learn by providing them with massive real-time data.AI works on either of two concepts augmentation or automation. Few AI systems are entirely automated or totally augmented since automation and augmentation are opposite extremes. While automation removes the need for any human activity, augmentation works on the concept of empowering humans to perform better. While strategizing the deployment of AI, it is important to consider what is the need of your organization and whether it should go for automation or augmentation. There is a strong chance that ethics will be prioritized poorly as businesses race to automate their business procedures. As it’s easy to mistakenly develop a discriminatory algorithm, one should be cautious while automating tasks. While deploying an AI model, taking consideration of having an ethical model is necessary toavoid lawsuits of any kind.


  • What is intelligence in AI ?

    Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment

  • What is deploying in AI?

    Deployment is the method by which you integrate a machine learning model into an existing production environment to make practical business decisions based on data.

  • How do you deploy an AI model?

    To deploy a model, you create a model resource in AI Platform Prediction, create a version of that model, then link the model version to the model file stored in Cloud Storage.

  • Is integration important in machine learning?

    Data integration remains essential for AI and machine learning.

  • What are the benefits of AI in business?

    Here are important benefits AI brings to businesses: 1 Efficiency and productivity gains. 2 Improved speed of business. 3 New capabilities and business model expansion. 4 Better customer service. 5 Improved monitoring. 6 Better quality and reduction of human error. 7 Better talent management.

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