AI and Transformations: The enterprise power couple
Discover how AI can streamline operations, reduce costs, and accelerate value creation, while addressing common transformation challenges.
The AI revolution has arrived鈥攁nd enterprise transformations will never be the same.
AI鈥檚 powerful suite of technologies has quickly become a force-multiplier for digital transformation initiatives and is delivering value for most companies, according to the 乐鱼（Leyu）体育官网 US Technology Survey Report, which found that 9 in 10 companies are now delivering improvements in profitability and performance from digital transformation initiatives.
However, AI is also revealing the weaknesses in many existing transformation projects by exposing cracks in their cloud and data foundations. These revelations are compelling innovation and transformation leaders to reevaluate their playbooks.
Indeed, when embedded seamlessly and intentionally into transformation projects from the start, AI鈥檚 game-changing technologies can help organizations streamline the notoriously complex 鈥渄etails鈥� of enterprise-change operations, reduce costs, as well as accelerate value creation and speed to market.
Clearly, AI technologies can play a starring role in enabling successful digital transformation initiatives鈥攁s our research and work with clients has shown.
But getting this power couple of AI and transformation to work in harmony will require companies to reimagine their approach, empower their people, and put some long-standing assumptions about how to deliver enterprise change in their rearview mirror.
Here鈥檚 a closer look at how AI technologies can enhance your digital transformation efforts.
Enhancing the transformation hierarchy
For many leading companies, reimagining the enterprise-change playbook starts with a commitment to making transformations that are AI-enabled from the start. They are using AI and GenAI tools to power key components at each level of the digital transformation journey鈥攆rom cloud-based-platforms to modern-data taking it all the way through to build AI-powered user experiences鈥攁nd tightly connecting these essential services at every level using modern composable architecture.
At 乐鱼（Leyu）体育官网, we think of this approach as an enhanced new transformation hierarchy: A framework for executing enterprise digital initiatives that leverages multiple cutting-edge capabilities, including Cloud, Data & AI (CDAI), to produce breakthrough efficiencies from the bottom up and the top down, powered by a fully connected Intelligent Cloud.
For leading enterprises, the goal of any business-led tech transformation is to deliver differentiated business outcomes. These leading enterprises leverage this modern transformation hierarchy and significantly optimize their user experiences via expanded customization for customers, employees, and their business and ecosystem partners. In our experience with client transformations, when they are done methodically by meticulously injecting AI and with hyper focus on value, they deliver not incremental but exponential business outcomes.
Here鈥檚 a closer look at how this dynamic new transformation hierarchy works:
The Engagement layer (Connectivity & Experience)
This layer leverages the platforms and data to deliver robust user experiences鈥攃ustomer-facing apps, predictive modeling for the finance team, and perhaps even a GenAI-powered executive dashboard to provide a near real-time view of how specific transformation initiatives are progressing.
The Cognitive Intelligence layer (Data & Integration)
This data and integration layer houses content, APIs, microservices, data pipelines and event-driven technologies.
The Engine Room (Platforms)
This foundational layer includes essential platforms like virtual ERPs, CRMs, data storage, and more. At this level, AI can help automate data extraction from legacy systems, as just one example, while GenAI can generate dynamic customer segmentations that support highly customized content and insights.
The Engagement layer (Connectivity & Experience)
The Engagement layer (Connectivity & Experience)
This layer leverages the platforms and data to deliver robust user experiences鈥攃ustomer-facing apps, predictive modeling for the finance team, and perhaps even a GenAI-powered executive dashboard to provide a near real-time view of how specific transformation initiatives are progressing.
The Cognitive Intelligence layer (Data & Integration)
The Cognitive Intelligence layer (Data & Integration)
This data and integration layer houses content, APIs, microservices, data pipelines and event-driven technologies.
The Engine Room (Platforms)
The Engine Room (Platforms)
This foundational layer includes essential platforms like virtual ERPs, CRMs, data storage, and more. At this level, AI can help automate data extraction from legacy systems, as just one example, while GenAI can generate dynamic customer segmentations that support highly customized content and insights.
4 common enterprise transformation traps
And how an AI-enabled approach can help avoid them
This new AI-enabled transformation hierarchy can help organizations improve outcomes and optimize value creation by eliminating many of the notorious transformation 鈥済otchas鈥� that have contributed to the methodology鈥檚 stubborn 鈥渙verpromise, underdeliver鈥� reputation.聽
1 | Executing on innovation
| Before | After |
| Random pilots, lack of coordination, and a 鈥渇ingers-crossed鈥� approach to proof of concepts. | AI focuses on business outcomes from the start. It provides a framework to prioritize efforts based on expected business value, identifies, and eliminates risks sooner, continuously monitors progress, and facilitates impactful change management. |
2 | Enhancing data
| Before | After |
| Legacy systems, data silos, redundant data, multiple ERPs, low-quality data, and time-consuming discrepancy reconciliations. | Intelligent cloud architecture harnesses data from all required systems, extracts meaningful insights, bypasses legacy obstacles, enables ongoing optimization, incorporates external signals, and provides a robust foundation for AI. |
3 |聽Future-proofing operations
| Before | After |
| Inconsistent data governance, cybersecurity gaps, and unaddressed privacy and compliance concerns. | A Trusted AI framework with automated risk monitoring, anomaly detection, recovery planning, scenario modeling, and compliance tracking for complex requirements. |
4 |聽Bringing your people along
| Before | After |
| Ineffective change management, lack of training, and unaddressed workforce fears. | Transformation efforts driven by cross-functional teams, commitment to training and upskilling staff, and centers of excellence to streamline adoption and scale innovations. |
Opportunity is knocking
For transformation leaders, help from AI isn鈥檛 鈥渙n the way鈥濃攊t鈥檚 here, today.
It鈥檚 already delivering real value and accelerating access to new capabilities for early adopters of their complex technology initiatives. And it鈥檚 upending stubborn, long-standing perceptions that most enterprise transformations are moonshots that, more often than not, fall short of their lofty goals.
To be sure, AI鈥檚 powerful (and still expanding) suite of technologies on their own aren鈥檛 some Rosetta Stones that will suddenly unlock the mysteries of successful transformations. But they can dramatically elevate the people, processes, and technologies involved.
Further, the debut of this new power couple doesn鈥檛 need to wait for some future enterprise change initiative. Indeed, many companies are achieving significant business value sooner by weaving AI into existing transformations.
With its power to turn complexity into clarity and moonshots into milestones, AI is proving that transforming the results from enterprise transformation doesn鈥檛 require a crystal ball 鈥� you just need to answer the opportunity knocking at your door.
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