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As the pace of change increases, even strategy can no longer afford to be a “one and done” paper exercise. And as business strategy and technology strategy become increasingly inseparable, technology is enabling strategic design, monitoring, and execution. Organizational products and services are increasingly digitized and digital, and organizations are exploring options to become platforms:

1. Strategy engineered
As the pace of change increases, strategy can no longer afford to be a “one and done” paper exercise. And as business strategy and technology strategy become increasingly inseparable, technology is enabling strategic design, monitoring, and execution. Organizational products and services are increasingly digitized and digital, and organisations are exploring options to become platforms.

2. Core revival
In a climate of historic uncertainty, ensuring that core systems can support new modes of work and mission critical innovation is more important than ever. Across industries, pioneering IT leaders are embracing a variety of new approaches and technologies to revitalize core assets. The impact of these efforts is being felt at the highest levels as CEOs, CFOs, and board members increasingly view core revitalization as an imperative to enable strategic change.

3. Supply unchained
Organizations are adopting an array of cognitive and digital technologies to transform vertical siloes of excellence with more integrated, horizontal supply chain models across internal functions. Their goal? Create greater agility throughout their supply chain networks so that when the next disruption takes place, they will be able to recapture lost productivity more quickly.

4. MLOps: Industrialized AI
To realize the full benefits of AI and machine learning, the era of artisanal AI must give way to one of automated, industrialized insights. Enter MLOps, the application of DevOps approaches to machine learning model development and delivery to help improve collaboration among teams , shorten development life cycles, and industrialize and scale machine learning development and deployment

5. Machine data revolution: Feeding the machine
Traditional data management attempts to organize a small, curated set of values for executive decision makers. As we move forward, organizations must rethink data management, storage and organization to take advantage of ML models. They must tune data for native machine consumption to achieve the desired benefits and scale of AI and MLOps.

6. Zero trust: Never trust, always verify
Moving to a cyber security posture of “zero trust” promises to resolve decades old security challenges and enable modern IT prac tices ( DevSecOps , NoOps ,Cloud, etc.) But moving to a “zero trust” posture will require significant effort including automating manual processes; improving foundational cyber hygiene;and planning for organizational and talent changes as enterprises move towards cyber engineering.

7. Rebooting the digital workplace
Organisations have migrated work and meetings from the physical to the digital workplace, but they’ve only scratched the surface of the possibilities. Analyzing the newly available data generated by remote workers, tools, and interactions their “digital exhaust” holds the promise of making individuals, teams and organisations more efficient and effective.

8. Bespoke for billions: Digital meets physical
Humans have been forced to embrace digital experiences faster than ever before. As a result, organizations are recognizing the need to reevaluate what and how they invest in technology and use data/analytics to build and tailor experiences to individual customer needs to determine the right balance between making traditional physical human experiences more digital, and digital experiences more physical.

9. DEI tech: Tools for equity
Organizations have access to increasingly sophisticated tools to help support their diversity, equity, and inclusion initiative. Many of these offerings use analytics to provide granular insight into such areas as talent acquisition, advancement, and retention. Others offer feedback a nd coaching capabilities for leaders and decision makers. All seek to make DE&I decision making and processes more data driven.