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Michael Papadopoulos

Partner

Chief Architect, Digital Problem Solving

United Kingdom

Michael is a strong advocate of the DevOps culture and agile principles, with demonstrated experience applying both in challenging global environments. Coming from a development background, he remains highly technical, with hands-on involvement.

Michael Papadopoulos

Areas of Focus

Education

University of Essex
B.Eng (1st Class) Computers & Networks

Past Experience

App-Art
Product architect
mSensis
Product architect

Michael Papadopoulos

Michael is a Partner at Arthur D. Little, based out of our London office, and serves as Chief Architect.

Michael is passionate about designing the right solutions using smart-stitching approaches, focusing on practicalities and realism over architectural purity. Michael is able to build and lead teams composed of software engineers, data scientists, designers, Q&As to deploy solutions solving apparently intractable problems with a focus on cloud-native applications.

Michael is responsible for creating new product offerings ranging from AI powered Technology Assessment across code & build quality, architecture, security and regulatory compliance to the SENSE Social Listening offering. Working with ADL colleagues and practices, these have been successfully deployed across the globe in a variety of industries including tightly regulated domains such as healthcare.

Michael has demonstrated experience in solving problems in challenging global environments. Coming from a development background, Michael remains highly technical, with hands-on involvement in code review, design, architecture, and operations. 

Taking control of AI
Taking control of AI
For decades, organizations have struggled to connect employees with the internal knowledge and insights they need to make better, more informed, and timelier decisions. Finding the right information, at the right time, among the increasing volumes of structured and unstructured corporate data, and delivering it in the right format is business-critical. However, it is often like looking for a needle in a haystack.
Find out more
Tightening the data belt
Tightening the data belt
Mark Rowland, Michael Papadopoulos, Lokesh Dadhich, Sri Rajagopal
The era of big data has delivered real business impacts across industries. However, increased data gathering has a downside; ever-growing data storage volumes and compute requirements lead to budgetary and operational constraints. Automatically generated log files silently drive this rapid, enormous data growth. This Viewpoint identifies how companies can successfully improve holistic log file management to deliver benefits by controlling costs, ensuring compliance, and unlocking data value.
Find out more
Excelling in a software-driven future
Excelling in a software-driven future
Agron Lasku, Michael Kolk, Martin Glaumann, Michael Papadopoulos
Software is rapidly becoming a critical asset as industries converge and perception of value shifts from hardware to software. Surgeons, for instance, can perform lifesaving surgeries via virtual reality (VR). But such a revolutionary procedure demands zero risk for error or downtime in connectivity, leading to new network requirements. Retail and commerce has also conjoined with computing, logistics, and finance for seamless online shopping.
Find out more
Blue Shift: The Metaverse, beyond fantasy
The Metaverse, beyond fantasy
Rick Eagar, Michael Papadopoulos
$ynth3t1( w0rld, r3al 3(0n0my [Synthetic world, real economy]
Find out more
Winning the war for digital talent
Winning the war for digital talent
Michael Papadopoulos, Michael Majster, Olivier Pilot, Alexey Pankov, Greg Smith
Businesses across the world are facing a shortage of professional talent and expertise in digital and IT skills and capabilities. For example, a 2021 survey suggested that 76 percent of IT decision-makers worldwide faced critical skills gaps in their departments, an increase of 145 percent since 2016.[1]
Find out more
Industrial goods & services
Why machine learning is crucial
Greg Smith, Michael Papadopoulos
This article explores the challenge of managing and gaining the most value from big data. We highlight the increased opportunity associated with larger data sets, while illustrating the limitations of current methods and human intellect across the 4 Vs of big data (volume, velocity, variety, and veracity), ultimately resulting in lost value — the fifth V. We further show how organizations can use machine learning (ML) to address these limitations and realize the full value from big data. Finally, we highlight how cutting-edge companies employ ML to obtain greater value.
Find out more

Michael Papadopoulos

Michael is a Partner at Arthur D. Little, based out of our London office, and serves as Chief Architect.

Michael is passionate about designing the right solutions using smart-stitching approaches, focusing on practicalities and realism over architectural purity. Michael is able to build and lead teams composed of software engineers, data scientists, designers, Q&As to deploy solutions solving apparently intractable problems with a focus on cloud-native applications.

Michael is responsible for creating new product offerings ranging from AI powered Technology Assessment across code & build quality, architecture, security and regulatory compliance to the SENSE Social Listening offering. Working with ADL colleagues and practices, these have been successfully deployed across the globe in a variety of industries including tightly regulated domains such as healthcare.

Michael has demonstrated experience in solving problems in challenging global environments. Coming from a development background, Michael remains highly technical, with hands-on involvement in code review, design, architecture, and operations. 

Taking control of AI
Taking control of AI
For decades, organizations have struggled to connect employees with the internal knowledge and insights they need to make better, more informed, and timelier decisions. Finding the right information, at the right time, among the increasing volumes of structured and unstructured corporate data, and delivering it in the right format is business-critical. However, it is often like looking for a needle in a haystack.
Find out more
Tightening the data belt
Tightening the data belt
Mark Rowland, Michael Papadopoulos, Lokesh Dadhich, Sri Rajagopal
The era of big data has delivered real business impacts across industries. However, increased data gathering has a downside; ever-growing data storage volumes and compute requirements lead to budgetary and operational constraints. Automatically generated log files silently drive this rapid, enormous data growth. This Viewpoint identifies how companies can successfully improve holistic log file management to deliver benefits by controlling costs, ensuring compliance, and unlocking data value.
Find out more
Excelling in a software-driven future
Excelling in a software-driven future
Agron Lasku, Michael Kolk, Martin Glaumann, Michael Papadopoulos
Software is rapidly becoming a critical asset as industries converge and perception of value shifts from hardware to software. Surgeons, for instance, can perform lifesaving surgeries via virtual reality (VR). But such a revolutionary procedure demands zero risk for error or downtime in connectivity, leading to new network requirements. Retail and commerce has also conjoined with computing, logistics, and finance for seamless online shopping.
Find out more
Blue Shift: The Metaverse, beyond fantasy
The Metaverse, beyond fantasy
Rick Eagar, Michael Papadopoulos
$ynth3t1( w0rld, r3al 3(0n0my [Synthetic world, real economy]
Find out more
Winning the war for digital talent
Winning the war for digital talent
Michael Papadopoulos, Michael Majster, Olivier Pilot, Alexey Pankov, Greg Smith
Businesses across the world are facing a shortage of professional talent and expertise in digital and IT skills and capabilities. For example, a 2021 survey suggested that 76 percent of IT decision-makers worldwide faced critical skills gaps in their departments, an increase of 145 percent since 2016.[1]
Find out more
Industrial goods & services
Why machine learning is crucial
Greg Smith, Michael Papadopoulos
This article explores the challenge of managing and gaining the most value from big data. We highlight the increased opportunity associated with larger data sets, while illustrating the limitations of current methods and human intellect across the 4 Vs of big data (volume, velocity, variety, and veracity), ultimately resulting in lost value — the fifth V. We further show how organizations can use machine learning (ML) to address these limitations and realize the full value from big data. Finally, we highlight how cutting-edge companies employ ML to obtain greater value.
Find out more

More About Michael
  • University of Essex
    B.Eng (1st Class) Computers & Networks
  • App-Art
    Product architect
  • mSensis
    Product architect