The Enterprise #Data And #AI Journey To The Cloud: Three Fundamental Milestones

Didem Un Ates
3 min readJan 23, 2021


It was a great pleasure to publish my first article in Forbes on Enterprise #Data and #AI Journey to #Cloud:

Council Post: The Enterprise Data And AI Journey To The Cloud: Three Fundamental Milestones (

Data & AI Journey to Cloud

Here is the article in full length:

2020 has been a whirlwind in the development and adoption of technology, especially data analytics, artificial intelligence and machine learning and automation. These technologies have let us tackle Covid-19 by focusing on, according to the Organization of American States, “understanding the virus and accelerating medical research on drugs and treatments, detecting and diagnosing the virus and predicting its evolution, assisting in preventing or slowing the virus’ spread through surveillance and contact tracing, responding to the health crisis through personalized information and learning [and] monitoring the recovery and improving early warning tools.”

In turn, the pandemic notably accelerated the development and adoption of technology. We at Accenture and the broader Microsoft ecosystem have witnessed the remarkable acceleration of cloud adoption and data and AI maturation in our clients’ digital transformation efforts.

While there are countless platform, product and solution options an enterprise can pick to match its priority business scenarios and use cases, a simple “data and AI journey to cloud” framework may help enterprises in terms of planning, solution mapping and the successful implementation of their specific data and AI journey.

This framework consists of three fundamental milestones:

1. Data Strategy And Modernization: Advance data capabilities and culture

2. AI-Powered Capabilities: Infuse AI across critical enterprise functions such as sales, customer service, operations or the supply chain

3. Intelligent Enterprise: Enable more automation and self-serve mechanisms to evolve toward an autonomous enterprise.

Before I expand on each of these milestones, it is worth mentioning that a successful data and AI journey to the cloud necessitates a thoughtful and collaborative kick-off:

• Have you discovered your cloud transformation and data and AI needs (e.g., priority scenarios and use cases)?

• Have you created value cases for these scenarios and use cases?

• Have you built a road map for your data and AI adoption, transformation and innovation?

If not, I would strongly recommend you to slow down so you can speed up later. Make sure you and your stakeholders agree on these crucial steps before you kick off your journey.

Now, let’s elaborate on these three milestones:

The first step starts with data. Defining your data strategy, establishing a data culture in your organization and modernizing your data estate accordingly are essential. Some of the steps that will accelerate your organization’s maturity in this milestone are as follows:

• Perform a data strategy assessment.

• Perform a data capability and maturity assessment.

• Enact a data strategy transformation.

• Embrace a data operating model.

• Follow a 30- to 90-day road map.

Once you have the data (i.e., your plumbing) sorted, you can now infuse AI/ML across your enterprise and implement various AI-powered capabilities for your employees, customers, partners and the broader community in line with your business needs and priority use cases. These capabilities may include virtual agents, SaaS AI solutions, AI-powered sales and supply chain insights, robotic process automation, and more.

I use the word “infuse” for this second phase because you must ensure that all these AI capabilities are enabled responsibly and ethically in the organization. When looking for a solution, it is important to identify low-code or no-code platforms, which are easy to adopt and use. This means that current employees can readily embrace these solutions to focus their time and attention on higher-value activities.

The next phase involves becoming an autonomous enterprise. In this phase, you must implement more automation and self-serve mechanisms so that humans and machines work more coherently, efficiently and effectively. This phase includes more RPA and power automation, end-to-end systems, AI-powered fraud and risk management, and more.

In 2020, we saw the majority of our clients in the first two phases. Given the economic conditions mainly resulting from the pandemic, 2021 will undoubtedly accelerate this journey further to phases two and three. Where does your company fall among these phases, and what can you do to progress even further this year?

I wish you all a happy, healthy and prosperous 2021.



Didem Un Ates

@Schneider Electric #Data #AI #XR #ResponsibleAI #Diversity #Inclusion # Sustainability Formerly @Microsoft @Upenn @CBS Views are my own