Navigating the Cloud: Opportunities, Challenges, and Innovations in Multi-Cloud Adoption and Gen AI Integration

CXOToday has engaged in an exclusive interview with Mohammad Wasim, Group VP Technology at Publicis Sapient.

1. How does multi-cloud adoption present both opportunities and challenges for businesses?

Opportunities: Multi-cloud environment often allows organizations to be agile and flexible. If the organizations have technical know-how and maturity to manage cloud to orchestrate different clouds technologies (based on Cloud compatibility list) or unify them, it propels innovation without the worries of scale, upfront CapEx that are typically associated with traditional IT footprint. With multi-cloud environment, organizations can maximize the usage of best-in-class features, without worrying about hardware lock-in or technology refresh, even cloud vendor lock in, if the architecture is portable. Multi-cloud adoption also helps in managing compliance requirements set by various data regulations, as organizations are in better position to manage outages, recover data due to redundancy and back-up, and move beyond the traditional worries of regional/local shutdowns. Thus, data recovery and security are often managed better with multi-cloud environment as it takes away the leg work that one need to do obtain compliance.

Challenges: Multi-cloud adoption can bring in business challenges, especially for those organizations where the cloud adoption is not backed by IT (or cloud) strategy. Some of the challenges that we have seen in less-mature organizations are:

• Managing operational aspects of cloud infrastructure – multiple partners, migration, number of instances in use, demand surge and ability to scale. This may impact pay-per use.
• Lack of clarity on roles and responsibilities, often resulting from lack of understanding of shared responsibility model w.r.t. data compliance, controls and cloud management
• Technical complexity (cloud architecture, stakeholder management) resulting from multi-cloud management may require further investment in skillset and talent training.

2. How can businesses foster a culture of innovation and agility amidst the growing reliance on cloud services?

Organizations can foster culture of innovation by focussing on the following –

• Leadership Alignment and commitment: As we have seen across multiple clients, the leadership alignment fundamentally elevates the ways of working:
  • Top-down approach within organizations help various teams such as Finance, Procurement, IT, Security etc., which previously may have been working in silos, come together and adapt to the new ways of working. For example, reliance on cloud services often shifts the worry from thinking about End-of-Life support or depreciation of the assets, upcoming Capital Expenses to more pay-as you-use approach. Leadership commitment drives convergence of these team, bringing in efficiency and coherence.
• Strategy: Defining the IT strategy, in alignment with business strategy keeping in mind the ones persona their IT maturity, is the first step towards innovation. By understanding the vision for next 3-5 years, leaders must develop IT roadmap, and tie IT investments with the business outcome. Operationalizing the strategy will also require IT leaders to think about impact of the technology on productivity, associated risks and (how these risks can be managed) and it can create the sense of awareness among management team about the investments and ROI.
• Governance / Roles and Responsibilities: Implementation of the strategy will require clear Governance structure and assignment of responsibility and accountability among the IT team. The structure must be such that representation from each of the growth areas of the organization (for example, security team, Cloud team, Finance, Procurement etc.) must be included. The team should have regular cadence to discuss the progress and use the session to explain business objective of making the investment and how this would foster innovation within the organizations.
• Investment: Leaders should tie the investment with the desired outcome and the timeline, based on the IT strategy. Before making any investment decision, do analysis of priority areas for the organization. For instance, directionally think about whether investing on all the areas make business sense or investment on top 3-4 areas such as innovative ideas on AI/GenAI and cloud makes more business sense.
• Education: Education and training on the new technologies, including cloud adoption will help different personas within an organization to think about the impact it has on their respective day-to-day work. For instance –
  • IT Operations team may have to reconsider the usage of the underlying services, as per the surge in demand. Since everything in cloud is software-defined, the team will have to bring in flexibility in addressing the usage.
  • Strategy team may have to think about time to market of various services that may be under development currently. As the result of cloud advancement and adoption, can these services be brought to market within 3 months (as opposed to earlier deadline of 6 or 9 months?)
• Skill development & Shift left: Cross-skilling and up-skilling are needed more so now, than they have been needed before. Due to new technologies such as AI, ML and cloud, organizations see convergence in the roles, responsibilities and job descriptions of various team members. For example, a data analyst may now be required to learn AI and add versatility beyond single coding language; a network manager may be required to understand how the whole of cloud infrastructure work, instead of focussing on single localized network area etc.

3. How can IT teams navigate challenges in transitioning to cloud-native applications and effectively manage applications across multiple cloud providers?

Navigating to the cloud can be challenging, especially if the organizations lack clear understanding of objectives that they want to achieve. Thus, the very first step before investing time and resources on transitioning to cloud is to develop cloud strategy (or broadly IT strategy) tied to business goals and objectives that one needs to achieve. It is often observed that lesser mature organization (with perspective of engineering journey) often try to adopt direct “Lift and Shift” approach, but it needs to be understood that one size fit all approach can lead to higher operational cost and risks within the organizations.

In our experience, one of the key aspects to think at the cloud strategy stage is segregation of applications into various categories – applications to retain (and hence not required to move to cloud), applications to retire or decommission, applications for re-hosting (or Lift & Shift migration), applications that need to be re-architected, applications that may require the team upgrade the infrastructure and finally applications that may warrant replacement. Thinking from these aspects, will help IT and cloud engineering team to focus the attention on applications are fits the requirement.

Once the cloud strategy is developed, the team must create the migration strategy that includes finalized assessment plan, migration plan, architectural designs for the landing zones, and the team must have up to date visibility on application inventory and value chain of information assets. Further, establishing the overall governance and RACI matrix for managing the migration to the cloud, will help the team to navigate the operational challenges early-on. It is also recommended to have Shared Responsibility model outlined before initiating the transition to cloud. This gives clear visibility to the internal IT/cloud team and CSP team on the roles each member play and helps clarify the action items and respective ownership, especially during unexpected business/network downtimes.

Once migrated, managing multi-cloud environment becomes critical aspect and many Infrastructure and Operations leaders are investing in AIOps platform with the desire to improve visibility and monitoring of IT Operations, w/ tech and business observability.

4. How are businesses leveraging the advancements in Gen AI to enhance their operations and customer experiences?

Businesses across industries are leveraging Gen AI across their value chain. Organizations are not only investing in developing the talent on Gen AI, but also investing on creating IPs to help accelerate the delivery of respective. Various use cases that are being developed using Gen AI are:

• Use Computer Vision capabilities.
• Demand forecasting
• Anomaly detection – This use case can be applied in various operations – be it in improving SIEM capability for Cybersecurity monitoring or finding defect in machines in a manufacturing plant.
• Product bundling recommendation
• Analysis of large datasets
• Simulation of marketing scenarios using AI models and many more

Looking closely at the application of Gen AI for pharma sector (for example), the Gen AI capabilities can be applied to create personalized content for marketing campaigns for regional consumers – Marketing tool powered by Gen AI allows marketing team to produce customized banners, emails, condensed medical publications etc. thereby supporting any global company to expand its reach and relevance. Another example of Gen AI application could also be using Computer Vision for detecting plant family and genus. The task is complex, given thousands of plant genus that exists, and the image quality (based on light condition, weather etc.) is not always reliable to successfully categorize the plant family. To solve the challenge, Gen AI can be used to create robust AI-computer vision-based solutions.

Furthermore, Gen AI is being increasingly used in DevOps, right from development of business logic, to moving across stages of development and operations life cycle. AWS Code Whisperer, CoPilot are some of the examples that have changed the way we develop digital IPs and interact with the technology. Gen AI and AI-powered tools and platforms have greatly reduced time to market the respective services to the consumers.

5. Considering the evolving landscape of user interfaces with Gen AI, how do you envision businesses adapting to meet diverse customer needs and preferences?

Influx of consumer Gen AI programs such as ChatGPT and Bard have made Gen AI standout, when compared to other technology developments. The impact of Gen AI can be felt in our day-to-day work life, from summarizing the report, drafting the meeting notes, generating code, fine-tuning language models to monitoring network and operational risks.

To fully leverage Gen AI and elevate customer experience, organizations need a different approach, approach involving creating personas of end-users (end-consumers and employees included).  Some of the personas are discussed below:

• From the developers’ perspective, Gen AI can help to generate code, accelerate API design and development, check compliance status of the APIs being used and more. CSPs such as AWS are introducing products that enhances the productivity of developers. For example, Amazon Q, which is an interactive assistant that provides guidance through conversational AI; Amazon CodeWhisperer generates code suggestions, ranging from snippets to full code.
• From Operation management perspective, Gen AI and AI powered tools help to work on large dataset, thereby enabling the operations team to monitor network vulnerabilities and provide alerts on real-time basis.
• From Sales organization perspective, Gen AI even helps summarize large RFPs into consumable chunks. This functionality helps Sales team to better understand and address all the requirements sought out by the potential clients in their request for proposals.
• Media and Advertising companies can generate concepts and creative assets based on product audience, channels, geography, and language using fine-tuned Gen AI models.

There are so many use cases that are being developed – some of them have been tested and successfully implemented, while there are others that are still in the initial conceptualization stage. Given Gen AI and AI-powered products and tools are new, the maturity and evolution of the use cases and the technology is sometimes beyond our comprehension at this stage.