AI Revolution: Achieve Digital Transformation in the Digital Era

Digital Transformation involves moving from the current state of digital to an ideal future state, which requires identifying an organization’s lean digital quotient using tools like Lean Digital Quotient Finder to establish its current digital state and form an ideal future digital state based on vision, mission and business goals.

I firmly believe that digital transformation does not result from just one technology like Artificial Intelligence alone; rather it occurs due to a fusion of multiple technologies such as IOT, Blockchain, Digital Twin, Mobile Device Management Systems (MDMS), AI/ML systems and VR/VR technology.

With this “5 Point Knowledge Capsule”, I aim to highlight the role AI can play in digital transformation.

Senior business executives must take great care in understanding how AI/ML/DL has unleashed new capabilities that can assist leaders and dramatically boost business performance.

The critical part of digital transformation is to understand the business language of technology, its capabilities and embrace them.

Here are the top five capabilities of AI that were previously unavailable to businesses but can now be effectively integrated to help digitally transform to the next level.


  • At its core are three capabilities of Artificial Intelligence that use analytics:
    • Predictive analytics tell us “What will happen”, while Prescriptive analytics tell us “What should be done if it does occur”. (Providing solutions is also part of their function).
    • Autonomous Analytics: Just sit back and let the system take over – autonomous analytics systems implement solutions without human interference or oversight
    • Examples:
  • Offering personalized recommendations to customers as well as timely responses to their needs. Examples: Detect customer behavior and preferences to enable personalized recommendations and timely responses to meet them.
  • Forecast demand, optimize inventory levels and streamline supply chain operations – all while cutting costs and increasing efficiency – with predictive analytics.
  • Cross-selling/upselling opportunities may also be identified automatically to increase sales revenue.
  • Autonomous Analytics allows self-driving cars to predict traffic congestion, suggest solutions (e.g. alternate routes), and implement them automatically (i.e. navigate towards chosen route).


Generative intelligence allows machines to create new content using existing data – whether it’s text, images, music, software code or design concepts. Generative Intelligence acts like a smart tool which turns learned information into novel outputs as depicted below.

Text GenerationLanguage Translation
Image GenerationData Synthesis
Audio GenerationCode Generation
Video GenerationMaterial Properties Generation
3D Models Generation 
  • Examples:
  • Efficiency Improvement:
    • Incorporating Design, Prototyping and Product Development using Autodesk
    • Customized Software Solutions including Automated Testing with Testim
    • Healthcare: Synthetic Data Generation from MDClone BioBERT GPT-4
    • Automotive: Vehicle Design Concepts (BMW Group, DALL-E and AutoML).
  • Customer Satisfaction:
    • Customized Customer Experiences via E-commerce (Shopify).
    • Custom Designed Prototyping in Fashion and Art for Stitch Fix (Stitch Fix).
    • Healthcare: Tailored Patient Communication (Conversa Health, GPT-3/GPT-4)
    • Automotive: Tailored User Manuals (GPT-3/GPT-4)
  • Cost Reduction:
    • Slashed Cost Reduction Solutions for Media and Entertainment Industries such as Music Production (AIVA).
    • Educational and Training Tools: Simulations and Scenarios (CAE Healthcare).
    • For retail use, dynamic advertising content including Albert, GPT-3/GPT-4 and DALL-E (Albert GPT-3 GPT 4 DALL E).

AI Capability 3: Computer Vision.

Computer vision in AI allows machines to take on human eyesight by seeing, understanding and acting like them. Below are a few examples:

  • Customer Experience: Visual search and recognition technologies enable customers to find products or services more quickly, improving the overall shopping experience. For example, when taking photos of unique flowers in magazines for identification purposes, an app instantly identifies and directs them online for purchase.
  • Operational Efficiency: Computer vision technology can automate quality control in manufacturing, reducing errors and increasing production efficiencies. For instance, when factory cameras detect flaws on circuit boards during assembly lines, robotic arms automatically remove them before assembly lines continue running.
  • Revenue Growth: Visual data analytics can uncover market trends and help businesses tailor offerings to customers’ preferences, such as when Fashion brand analyses Instagram photos to find unexpected popularity of green sneakers – and launches limited-edition collection that sells out within 24 hours!

AI Capability 4: Recommender Engines.

Discovering your next must-watch, must-read or must-own item before realizing you want it is a powerful force of discovery. A few examples are given below:

  • Customer Experience: Customized product recommendations can significantly enhance customer satisfaction and loyalty. For instance, when browsing sofas online they are provided with recommendations of suitable coffee tables and rugs based on their style preferences for seamless room design experiences.
  • Revenue Growth: Recommendation engines can amplify upselling and cross-selling opportunities to drive increased sales revenue, such as Amazon or Netflix’s “Customers who bought this also bought” recommendations that drive cross-selling for added revenue growth.

AI Capability 5: Process Automation

Automating time-consuming and repetitive tasks allows humans to focus more effectively on valuable activities. A few examples are given below:

  • Operational Efficiency: Robotic Process Automation (RPA) can streamline repetitive tasks to cut operational costs and human errors. RPA bots perform back-office duties such as data entry and account updates quickly with high accuracy reducing processing time and errors significantly; furthermore, intelligent machines work alongside humans performing tasks such as part picking, assembly, and welding for increased productivity while reducing worker strain.
  • Employee Delight: Automating routine tasks can free employees to focus more on creative and strategic aspects of their roles, leading to higher job satisfaction. For instance, an RPA bot takes over repetitive social media posting and schedule management responsibilities, freeing the team up to focus on developing creative content and strategy resulting in increased campaign engagement and employee morale.


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