As we prepare for Google Cloud Next 2024, we reflect on the conversations we had at last year’s flagship Google Cloud event. This blog post explores the future of financial services, focusing on the role of artificial intelligence (AI) and cloud computing. 

Episode 46 – Future of financial services with Zac Maufe, Head of financial services industry solutions, Google Cloud 

In this episode between Zac Maufe, Google Cloud’s Head of Financial Services Industry Solutions, Dave Chapman and Rob Kernahan, the hosts of the Cloud Realities podcast, the conversation explores the challenges and opportunities presented by these new technologies. 

Financial Services – the big cloud catch-up 

The financial services industry has historically been behind the race in cloud adoption, owing to stricter regulations, complex legacy systems, and data fragmentation. While banks have been cautious about migrating sensitive financial data to the cloud, times are changing. With regulatory frameworks adapting, and the benefits of cloud computing – scalability, agility, and cost-efficiency – becoming increasingly attractive, the cloud catch up is a current reality. 

So what cloud options are financial services firms exploring? 

Core transformation and data liberation 

Financial institutions are now exploring various cloud-based solutions, including: 

• Core infrastructure modernization. Evaluating options like cloud-native core systems or “lift and shift” approaches to migrate mainframe workloads. 
• Data transformation. Breaking down data silos and leveraging cloud-based data management tools can uncover new insights and improve decision-making. 

Operation AI exploration 

AI, particularly LLMs, is a major area of exploration for financial services. Here are some potential applications: 

• Enhanced employee productivity. LLMs can assist analysts and coders, allowing them to work faster and handle more complex tasks. 
• Improved customer service. LLMs can power chatbots and virtual assistants, offering faster and more efficient support. 
• Risk management and fraud detection. AI can analyze large amounts of data to identify patterns and flag potential risks. 

Security and compliance in focus

While AI offers exciting possibilities, security and compliance remain paramount in financial services. Here’s how these concerns are being addressed: 

• Data ownership and control. Financial institutions retain ownership of their data throughout the AI process. 
• Security integration. Cloud-based AI tools leverage the same security controls as other Google Cloud Platform services. 
• Model governance. Establishing frameworks to ensure the explain ability, traceability, and responsible development of AI models. 

Regulation: Keeping pace with innovation 

Regulations surrounding AI are expected to evolve alongside the technology. Collaboration between regulators and the financial services industry is crucial to ensure responsible innovation and consumer protection. 

Conclusion 

The future of financial services is shaped by cloud adoption and AI. As cloud platforms become more secure and compliant, and AI capabilities mature, financial institutions will be better equipped to navigate the ever-changing landscape and deliver exceptional value to their customers. 

Preparing for Google Cloud Next 2024 

We’ll be at Google Cloud Next with podcasts, exclusive client sessions and demos exploring exactly how we are transforming financial services with cloud, Data/AI, and software engineering on Google Cloud. 

Innovation, meet intelligence. 

Explore the power of our collaboration with Google Cloud. 

As we prepare for Google Cloud Next 2024, we reflect on the conversations we had at last year’s flagship Google Cloud event. This blog post explores the concept of experience-led cloud transformation.

Episode 47 – GoogleCloudNext23: Experience led cloud transformation with Mahin Samadani, Director of strategic business transformation, Google Cloud

Drawing on a conversation between Dave Chapman, Rob Kernahan our Cloud Realities podcast hosts, and Mahin Samadani, Director of Business Transformation at Google Cloud, we explore why cloud transformation is no longer just about technical migration. It’s about fundamentally changing how businesses operate and deliver value. This blog post dives into experience-led cloud transformation, a strategic approach that prioritizes user experience (UX) at every stage.

The shift to experience-led cloud transformation 

Traditionally, cloud transformation has been viewed as a technical exercise. However, businesses are increasingly recognizing the importance of UX in driving success. Mahin emphasizes that cloud adoption should be anchored in user experience design principles. It allows you to understand your cloud transformation in a way that you can prioritize everything in behind delivering UX. And every dollar spent or every or every line of code is impacting the end user or the end customer. This means that businesses should start by understanding their user needs and then use cloud technologies to create solutions that meet those needs.  

Rob Kernahan raises an important point: cloud transformation is often seen as a technical endeavor, neglecting the human aspects of change. Mahin emphasizes the need for a holistic approach that considers not just technology but also change management, culture, talent, and purpose. 

Mahin shares some examples of how businesses are using experience-led cloud transformation to achieve success, such as: 

• Hackensack Meridian Health: Google Cloud found that for every hour a care provider spends providing care to a patient, they spend two hours on administrative tasks. Making that more efficient through experience-led cloud transformation, perhaps through transcription, automation, etc. could provide a significant benefit to the client and to the business. 
• Netflix: Listens to their users to pivot their business – not just necessarily in a qualitative sense, but by looking at their data really carefully, they’re able to take calculated risks and pivot and change and introduce, new capabilities and features. 

Design thinking for cloud transformation 

The conversation highlights the value of Google Ventures Design Sprints, a user-centered methodology that facilitates rapid prototyping and testing of new ideas. This approach helps organizations understand user needs, identify opportunities, and develop cloud-based solutions that deliver real value. 

Key considerations for experience-led transformation 

• The power of purpose. Having a clear purpose is essential for driving successful transformation. A strong purpose provides direction, motivates employees, and helps stakeholders understand the “why” behind the change. 
• User Focus. Prioritize understanding and meeting user needs throughout the transformation journey. 
• Data-driven decisions. Leverage data to inform decisions, optimize user experiences, and measure the success of initiatives. 
• Experimentation. Embrace experimentation and iteration to continuously improve experiences and drive innovation. 
• Platform adoption. Utilize cloud platforms to facilitate rapid development, deployment, and scaling of user-centric solutions. 
• Change management. Develop a comprehensive change management strategy to address employee concerns and ensure successful adoption of new tools and processes. 
• Culture of innovation. Foster a culture that values creativity, experimentation, and continuous improvement. 

Conclusion 

We all know cloud is not a destination, it’s a journey. Experience-led cloud transformation presents a powerful approach to unlocking business value in the cloud era. By prioritizing user experience, adopting a holistic mindset, and embracing a culture of innovation, organizations can leverage the cloud to create new opportunities, improve operational efficiency, and achieve sustainable growth. 

Preparing for Google Cloud Next 2024 

We’ll be at Google Cloud Next with Cloud Realities podcasts recording daily, exclusive client sessions and demos exploring exactly how we are embracing experience-led cloud transformation with our clients across all industries, on Google Cloud. 

Innovation, meet intelligence. 

Explore the power of our collaboration with Google Cloud. 

As we prepare for Google Cloud Next 2024, we reflect on the conversations we had at last year’s flagship Google Cloud event – a hub of innovation and insightful conversations, and of course, many of the most compelling discussions revolved around the transformative power of GenAI. 

In this blog post, we’ll delve into the captivating dialogue between our hosts and Rodrigo Rocha, Global ISV Leader for AI and Applications Partnerships, Google Cloud, as they explored the practical and exciting alternate realities unleashed through cloud-driven transformation. 

Episode 44 – AI is centre stage with Rodrigo Rocha, Director Global Horizontal Partnerships, Google Cloud  

Our hosts, Dave Chapman, and Rob Kernahan shared their experiences and expectations for the conference. As they set the stage for the discussion, it became evident that GenAI was at the forefront of their minds.  

The exponential growth of the partner ecosystem 

Rodrigo, with his expertise in managing ISV applications and AI partnerships for Google Cloud, provided his unique insights into the evolving landscape of AI partnerships. He emphasizes the growth of the partner ecosystem, with a surge in AI startups and established companies seeking to infuse generative AI into their applications. The shift towards enterprise adoption of generative AI is noteworthy, marking a significant departure from the initial consumer-centric focus. 

As the conversation dove into the practical applications of AI, the attention steered to the aviation industry. How will AI streamline air travel, enhance airport logistics, and improve the overall flying experience? The potential for AI to transform customer service through chatbots and real-time data management was also highlighted, reiterating the diverse impact of AI across industries. 

Challenges of applying AI to drive business value 

Rodrigo emphasized the importance of aligning AI initiatives with clear business outcomes, marking a shift from the initial experimentation phase to a more strategic approach. This topic touched on the significance of responsible AI, with a strong emphasis on safeguarding data and ensuring ethical AI practices. 

The hosts and Rodrigo also explored the societal impact of AI, emphasizing the need for responsible stewardship in integrating AI into the fabric of our daily lives. The concept of democratizing AI and empowering users to harness its potential while maintaining robust security measures was a key theme that resonated throughout the conversation. 

The dialogue concluded with a preview of the key themes expected to emerge at the conference, including AI’s role in driving productivity, leveraging real-time data, multi-cloud technology, democratization of AI, and the top importance of security in the AI landscape. 

Conclusion

This episode from Google Cloud Next offers a compelling glimpse into the transformative power of Gen AI and its profound impact on diverse industries. From enhancing customer experiences to driving productivity and democratizing AI, the potential of Gen AI to reshape our world is both exhilarating and thought-provoking.  

No, Gen AI is not just a technological advancement. It’s a catalyst for a creative transformation that has the potential to redefine the way we live, work, and interact with the world around us. And we can’t wait to explore this with you at Google Cloud Next. 

Preparing for Google Cloud Next 2024 

And while we will continue to explore generative AI, we will dive into strategies and solutions in cloud, Data/AI, and software engineering at Google Cloud Next 2024 with a whole new host of Cloud Realities podcast guests. 

Innovation, meet intelligence. 

Explore the power of our collaboration with Google Cloud.

Imagine a future where enterprises don’t just aim to become data powerhouses but do so sustainably, ensuring both technological advancement and planet preservation.

Tapping into the vast data sources for improved products and digital services is crucial. Yet, in our race for innovation, sustainability emerges as a pivotal cornerstone, safeguarding both our planet and a company’s future relevance. The secret sauce? A sustainable data value chain. Dive in as we explore the essence of green data, drawing insights from the Green Software Foundation.

In recent years, enterprises followed the goal of becoming data-powered enterprises to leverage the full potential of data for their value chain. Levering the insights from all the sources of relevant data to create improved and new products and additional (digital) services is the top priority for enterprises. But sustainability has become a main goal for businesses too, to preserve the planet and the company’s relevance in the next decades.

The Greenhouse Gas Protocol defines three scopes (scope 1, scope 2 and scope 3) to delineate direct and indirect emission sources, improve transparency, and provide utility for different types of organizations and different types of climate policies and business goals. Through this framework companies can define and manage their emissions.

But this is only the first step. With clarification of emissions within the three scopes, companies get transparency on what’s happening within the value chain and clarity on where to reduce. But the main challenge is to know how to reduce their emissions.

Here, the Green Software Foundation has defined six principles to be applied in software development:

1. Carbon efficiency: Emit the least amount of carbon possible.
2. Energy efficiency: Use the least amount of energy possible.
3. Carbon awareness: Do more when the electricity is cleaner and do less when the electricity is dirtier.
4. Hardware efficiency: Use the least amount of embodied carbon possible.
5. Measurement: What you can’t measure, you can’t improve.
6. Climate commitments: Understand the exact mechanism of carbon reduction.

For each of the six principles, examples on achieving them are available, especially on the area of carbon awareness. Not only have the big hyperscalers (AWS, Azure, Google) made this topic a top priority, but also dedicated smaller solutions can be found. Two innovative examples are Green Mountain, which provides 100 percent renewable energy sourced data centers for co-location in Norway, and windCORES, which helps companies deploy small, co-location data centers in wind turbines, provided by 100 percent renewable energy and maximizing the used space from the wind turbines. With Green Data Engineering, a first view on how to apply these principles to data engineering have been laid-out.

But one question remains: how can companies aiming to be data-powered enterprises do this in a sustainable way? The answer sounds simple and complex in the same way: apply the principles of the GHG framework towards the data value chain and make the carbon footprint of data products and use cases transparent.

This is not as complicated as it sounds; most information is already available.

With the Carbon Aware SDK  from the Green Software Foundation and the Sustainability APIs, SDKs, and dashboards from hyperscalers, it is possible to calculate the carbon footprint of applications and processes. As an example, the Azure Sustainability Manager provides a comprehensive overview with multiple reports on the customer landscape running on Azure. But this is limited to one cloud. What about the more common example of customers running multi-cloud environment strategy?

Modern applications are composed of many smaller pieces of software (components) running on many different environments, for example: private cloud, public cloud, bare-metal, virtualized, containerized, mobile, laptops, and desktops.

Every environment requires a different model of measurement, and there is no single solution to calculate the environmental impacts for all components on all environments.

To achieve this, the Green Software Foundation has incubated the Impact Framework (IF). The IF is a framework to Model, Measure, simulate, and Monitor the environmental impacts of software. It allows you to define a calculation manifest file, a YAML file which describes the calculation of emissions. So rather than just saying “Carbon is X” you can say “Carbon is X and here is all the data, all the working out, and all the assumptions and models that we used.” You can run the YAMLs to confirm a claim and if you don’t agree with some of the data, models, and assumptions, you can change and run it again to see how that alters the value.

IF represents the carbon footprint of different components in a graph to aggregate the information and draw dependencies and interconnections.

• Configuration describes shared information regarding this component and, most importantly, parameters required by this model.
• Observations are a time series of data points used as inputs to the model.
• Model is a plugin which when given some configuration and a series of observations can calculate the impact, e.g. carbon impact from an observation of CPU utilization.

With this approach, it’s possible to aggregate up the carbon footprint of software components of applications easily. And by proper application of portfolio management, the mapping of application-based carbon footprint along the value chain is mainly pure calculations.

We might wonder how about data products and use cases? Didn’t we want to be data-powered? Sure, just as a small recap: The “data product, the architectural quantum is the node on the mesh that encapsulates three structural components required for its function, providing access to the domain’s analytical data as a product as Martin Fowler mentions in his article. They are:

• Code
• Data and metadata
• Infrastructure

Sounds familiar? Right, it’s easily comparable to any other application. Therefore, the transfer of the Impact Engine Framework towards a Data Mesh approach is not as hard as it sounds.

And with that, companies have the right tooling in place to ensure ESG compliance for their data-powered enterprise journey. And as the whole value chain transformation towards more digital services and products continues, the importance of mapping their carbon footprint along the data value chain is essential. Not only to be compliant with ESG reporting, based on the scope 3 disclosures required under the European Union’s Corporate Sustainability Reporting Directive, which comes into force January 2024, but also to maintain the Race to Zero. The race is still on, and it’s a data-powered race.

“LEVERING THE INSIGHTS FROM ALL THE SOURCES OF RELEVANT DATA TO CREATE IMPROVED AND NEW PRODUCTS AND ADDITIONAL (DIGITAL) SERVICES IS THE TOP PRIORITY FOR ENTERPRISES. BUT SUSTAINABILITY HAS BECOME A MAIN GOAL FOR BUSINESSES TOO, TO PRESERVE THE PLANET AND THE COMPANY’S RELEVANCE IN THE NEXT DECADES.”

INNOVATION TAKEAWAYS

COMPLIANCE = TRANSFORMATION

Enterprises need to comply with the EU’s Corporate Sustainability Reporting Directive, which has an impact on the transformation towards more digital services and products.

THE SOLUTIONS ARE IN THE CLOUD

Hyperscalers provide solutions within their environments to tackle carbon footprint.

AN OPEN FRAMEWORK

With the IEF by the Green Software Foundation, a framework for overarching carbon impact calculations exists.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 7 features 16 such fascinating articles, crafted by leading experts from Capgemini, and partners like Aible, the Green Software Foundation, and Fivetran. Discover groundbreaking advancements in data-powered innovation, explore the broader applications of AI beyond language models, and learn how data and AI can contribute to creating a more sustainable planet and society.  Find all previous Waves here.

We boiled down this year’s biggest conference into 10 key trends that (surprise) revolve around AI’s most promising benefits and practical applications.

In January, the 2024 Consumer Electronics Show – CES® – unleashed a swarm of emerging technologies that are driving both present and future advancements. The prevailing theme? Artificial Intelligence. With 2023 dubbed the “Year of AI,” we weren’t that shocked to see AI ubiquitous in all facets of innovation showcased at CES; from wearables and immersive technologies to robotics and semiconductor chips.

Beyond mere buzz, brands flocked to CES eager to explore the tangible applications of AI. In the aftermath of CES, we’ve distilled our observations into 10 trends spanning five key pillars, each exemplifying AI’s key benefits: Knowledge Enhancement, Convenience and Safety, Immersive Experiences, Augmented Decision Making, and Efficiency.

Read on as we unpack these industry-defining trends.

Pillar #1: Knowledge Enhancement

AI’s power to unlock unprecedented insights into our health and the world around us signals a leap towards more informed and frictionless living.

Trend #1: DIY Diagnosis.

Forget looking up your symptoms on WebMD.com, health management is getting personal and proactive with at-home diagnostics tools. Wearables, facial scans, at-home urine tests, and more provide real-time insights and personalized health recommendations, empowering users to take charge of their well-being.

•  Impact:
  –For Consumers: Detect symptoms early for better health outcomes.
  -For Businesses: Generate more frequent yet meaningful consumer touch points.
•  Thought Starter: How might a life sciences company collaborate with research institutions and startups to create accessible self-diagnosing products and complementary services?
•  What We Saw at CES: Withings’ BeamO device offers a complete at-home health checkup in just one minute, including insights into your heart and respiratory system. Another one we liked was FaceHeart, which provides information on your vitals in 60 seconds or less using AI image recognition technology.

Trend #2: Intelligent Accessories.

Brace yourselves for the biggest fashion trend of the decade: AI hardware accessories are officially “IN.” These aren’t your run-of-the-mill gadgets; they’re wearable computers that seamlessly integrate into our lives. From capturing photos intuitively to transcribing notes, these accessories are redefining our relationship with technology.

•  Impact:
  –For Consumers: Enable seamless and personalized services and experiences.
  –For Businesses. Reach and engage with customers in the moments that matter.
•  Thought Starter: How might a major theme park operator use AI-powered accessories to enhance visitor experiences by providing real-time information about queue wait times and unlocking interactions with beloved film characters?
•  What We Saw at CES: Of course, everybody was talking about Meta’s Ray Ban collection and the rabbit r1 — two prime examples of how we see this trend unfolding in the market — but we wanted to spotlight another example: Wisear, a Techstars backed startup, enables consumers to achieve voiceless and touchless controls over their everyday devices through its patent-pending neural decoding technology, Wisearphones.

Pillar #2: Convenience & Safety

Through AI, our homes and cars are becoming guardians of our well-being, adding layers of convenience and safety to our lives.

Trend #3: Robotic Helping Hands.

The average household is getting larger…in the form factor of a small, mobile, metal companion. Robotic adoption is primed to accelerate due to advancements in machine learning, autonomous software, and rising consumer demand for security and convenience. These robots streamline daily tasks, from making coffee to keeping an eye on the dog when you are away from home.

•  Impact:
  – For Consumers: Achieve greater convenience and safety in the home.
  –For Businesses: Unlock a wealth of new insights pertaining to the home and homeowner behavior to fuel meaningful growth opportunities.
•  Thought Starter: How might a P&C insurer leverage robotics to bolster the safety and well-being of homeowners — from detecting potential leaks to assisting with day-to-day chores?
•  What We Saw at CES: Ogmen Robotics supports family care through robotic companions that monitor and care for the well-being of pets, children, and the elderly. We also took note of larger tech players dropping their own robotic home care companions, including Samsung’s Ballie and LG’s two-legged Smart Home AI Agent.

Trend #4: Smart(er) Cars.

Fully autonomous cars may not be mainstream, but drivers are steadily lifting fewer fingers as AI-powered advancements make driving safer and more intuitive. From autonomous features to personalized hands-free assistance, cars are becoming smarter companions on the road.

•  Impact:
  -For Consumers: Benefit from improved safety and personalized in-car experiences.
  –For Businesses: Uncover new revenue opportunities through value-added software services.
•  Thought Starter: How might an OEM use AI and autonomous technologies to reduce the stress of driving and create a more streamlined in-car experience?
•  What We Saw at CES: Leveraging generative AI and Amazon Alexa, BMW’s new Intelligent Personal Assistant can converse with drivers and carry out functions like climate control, lights, media, and experience modes.

Pillar #3: Immersive Experiences

AI is redefining customer interactions by supercharging immersive experiences that were once the stuff of science fiction — shifting immersive experiences from a nice-to-have to a must-have competitive advantage.

Trend #5: Screen 3.0.

It’s not just bigger and better, screens are evolving beyond size and resolution, offering immersive, interactive, and versatile experiences. Whether it is augmented, touchless, transparent, or projected, screen advancements are transforming how we engage with digital content.

•  Impact:
  -For Consumers: Enable more hygienic and intuitive user interactions.
  –For Businesses: Drive increased brand awareness, engagement, and conversion.
•  Thought Starter: How might an airline leverage touchless and 3D screen technologies to make displays more engaging and hygienic?
•  What We Saw at CES: Leia, a 3D technology company (named after the Princess Leia hologram in Star Wars Episode IV), is pioneering holographic experiences on any device to create a digital future as rich as our 3D world. We also recommend you check out Hypervsn, creating next-gen signage for companies like LVMH, and Ultraleap, which is retrofitting digital interfaces to make them touchless.

Trend #6: Build-a-Metaverse.

Metaverse may have taken a back seat this year, but thanks to AI, it’s becoming more of a reality and less of a sci-fi concept. AI is transforming the metaverse in two ways: 1) Making it easier to build, 2) Enabling more personalized user experiences. From gaming to learning, the metaverse offers limitless possibilities for high-engagement brand interaction.

•  Impact:
  –For Consumers: Uncover more personalized, accessible, and informative brand experiences.
  –For Businesses: Unlock a new channel to reach customers, particularly the younger, gaming-native generations.
•  Thought Starter: How might a beauty retailer create a virtual branded store using AI and metaverse technologies to offer a more personalized, accessible, and informative shopping experience?
•  What We Saw at CES: Obsess, a top experiential e-commerce platform, powers immersive, interactive 3D, and 360-degree virtual experiences for Fortune 500 brands. It’s compatible with desktop, mobile, and Apple Vision Pro. Explore the new Crate & Barrel virtual flagship store here.
  

Pillar #4: Augmented Decision Making

AI aids in complex decision-making processes, providing clarity and precision in the business units that matter most.

Trend #7: Consumer Bullseye.

The margin for error of who to target, when, how, and with what content is dwindling as AI empowers marketing and sales to directly resonate with target customers. There is a decreased reliance on guesswork that can lead to ineffective campaigns, as AI tools help target the right customers at the right time with the right content.

•  Impact:
  –For Customers: Unlock more personalized and relevant touch points.
  –For Businesses: Optimize marketing and sales strategies.
•  Thought Starter: How might a luxury fashion brand use AI to analyze qualitative data from social media and surveys to uncover changes in customer sentiment over time?
•  What We Saw at CES: Glimpsehere uses cutting-edge generative AI capabilities to help businesses gain insights into qualitative feedback at scale and test marketing messages with virtual personas.

Trend #8: Sticky Success.

Through AI, R&D is becoming less art and more science, enabling teams to launch innovations more likely to stick in the market. Tasks like searching for patents, identifying market gaps, and validating ideas can be bolstered by AI to accelerate innovation and market success.

•  Impact:
  –For Customers: Access more frequent, relevant, and affordable innovations.
  –For Businesses: Achieve faster innovation at reduced costs.
•  Thought Starter: How might a beverage company use AI to identify and validate top flavor combinations of 2025 that are most likely to resonate with Gen Z customers?
•  What We Saw at CES: Prelaunch connects innovative products with potential customers before market entry. Another one of its features includes an AI Market Research Assistant that reviews and assesses competitor praises and complaints to uncover market opportunities.

Pillar #5: Efficiency

The drive towards efficiency is finding its champion in AI, optimizing operations across industries for better outcomes.

Trend #9: Company Clone.

Seeing double? Companies with a physical footprint are making digital copies. AI, IoT, and digital twin technologies enable companies to create dynamic virtual replicas of their properties, people, and processes to not only better understand their present, but better predict the future.

•  Impact:
  -For Customers: Enhance decision-making with real-time information and recommendations.
  –For Businesses: Gain real-time and predictive insights into operations to more efficiently address potential issues.
•  Thought Starter: How might a Tier One Supplier leverage digital twin technologies to design an offering that helps OEMs better predict and prevent failures in their vehicles?
•  What We Saw at CES: In a CES ’24 keynote, the CEO of Siemens fully endorsed digital twins and discussed plans to build an ‘Industrial Metaverse’ with NVIDIA, enabling companies to monitor their physical assets in real time.

Trend #10: Cloud-Free Days.

We are entering an era of less loading lags as AI at the edge brings intelligence closer to the source, enabling us to enjoy faster, smarter, and more secure experiences, without reliance on the cloud or internet. From smart devices to autonomous systems, digital experiences are thriving with AI at the edge.

•  Impact:
  –For Customers: Unlock faster and more reliable device performance.
  –For Businesses: Drive lower data transmission costs and latency.
•  Thought Starter: How might a fleet operator leverage AI at the edge to optimize routing and delivery, and enhance warehouse automation?
•  What We Saw at CES: NVIDIA released new AI chip modules powering on-device AI applications that are embedded in anything from delivery robots to autonomous mining vehicles.

Bringing these trends to life

CES 2024 was a resounding call for businesses and individuals alike to adapt to an AI-infused future. Understanding and integrating these AI applications is no longer optional but essential for thriving in a rapidly evolving world.

At the Applied Innovation Exchange, we help businesses experiment and explore new technologies so that they can bring transformative, industry-leading innovations to market. We enable this through our rich and diverse ecosystem of experts, startups, alliance partners, and Capgemini capabilities to deliver pinnacle innovation engagements: Workshops, experimentations, functional prototypes, and ecosystem collaborations. Get in touch with us today to learn more and find out how you can step into tomorrow.

Generative AI is reshaping business operations and customer engagement with its autonomous capabilities. However, to quote Uncle Ben from Spiderman: “With great power comes great responsibility.”

Managing generative AI has been challenging as generative AI models are outperforming humans in some areas, such as profiling for national security causes. Sometimes, anti-principles clearly explain why ethics must be enforced, so it is important to understand the following challenges:

• Generative AI can assist in managing information overload by helping extract and generate meaningful insights from large volumes of data but, at same time, information overload can dilute precise messaging.
• A lack of domain-specific knowledge or context leads to inaccurate information and contextual errors in addition to bias and subjectivity.
• There may be limited human resources to oversee training and regulate output, due to a lack of experienced personnel.
• Stale data may be used in training.
• Elite and/or not always ethically sourced data may be used for training.
• There may be a lack of resilience in execution.
• Scalability and cost tradeoffs may cause organizations to consider a shortcut.

Although complex, these challenges can be alleviated on a technical level. Monitoring is a good example of ensuring robustness and observability of the behavior of these models. Additionally, since generative AI capability is exposing businesses to new risks, there is a need for well-thought-through governance, guardrails, and the following methods:

• Model benchmarking
• Model hallucination
• Self-debugging
• Guardrails.ai and RAIL specs
• Auditing LLMs with LLMs
• Detecting LLM-generated content
• Differential privacy and homomorphic encryption
• EBM (Explainable Boosting Machine)

It is crucial that generative AI design takes care of the following aspects of ethical AI:

• Ensuring ethical and legal compliance – Generative AI models can produce outputs that may be biased, discriminatory, or infringe on privacy rights.
• Mitigating risk – Generative AI models can produce unexpected and unintended outputs that can cause harm or damage to individuals or organizations.
• Improving model accuracy and explainability – Generative AI models can be complex and difficult to interpret, leading to inaccuracies in their outputs. Governance and guardrails can improve the accuracy of the model by ensuring it is trained on appropriate data and its outputs are validated by human experts.
• Ethical generative AI approaches need to be different based on the purpose and impact of the solution, so diagnosing and treating life-threatening diseases should have a much more rigorous governance model than using generative AI to give marketing content suggestions based on products. Even the upcoming EU AI Act prescribes risk-based approaches, classifying
• AI systems into low-risk, limited or minimal risk, high-risk, and systems with unacceptable risk.
• AIs must be designed to say “no,” a principle called “Humble AI.”
• Ethical data sourcing is particularly important with generative AI, where the created model can supplant human efforts if the human has not granted explicit rights.
• Inclusion of AI: most AIs today are English-language only or, at best, use English as a first language.

USING SYNTHETIC DATA FOR REGULATORY COMPLIANCE

Försäkringskassan, the Swedish authority responsible for social insurance benefits, faced a challenge in handling vast amounts of data containing personally identifiable information (PII), including medical records and symptoms, while adhering to GDPR regulations. It needed a way to test applications and systems with relevant data without compromising client privacy. Collaborating with Försäkringskassan, Sogeti delivered a scalable generative AI microservice, using generative adversarial network (GAN) models to alleviate this risk.

This solution involved feeding real data samples into the GAN model, which learned the data’s characteristics. The output was synthetic data closely mirroring the original dataset in statistical similarity and distribution, while not containing any PII. This allowed the data to be used for training AI models, text classification, chatbot Q&A, and document generation.

The implementation of this synthetic data solution marked a significant achievement. It provided Försäkringskassan with realistic and useful data for software testing and AI model improvement, ensuring compliance with legal requirements. Moreover, this innovation allowed for efficient scaling of data, benefiting model development and testing.

Försäkringskassan’s commitment to protecting personal data and embracing innovative technologies not only ensured regulatory compliance but also propelled it to the forefront of digital solutions in Sweden. Through this initiative, Försäkringskassan contributed significantly to the realization of the Social Insurance Agency’s vision of a society where individuals can feel secure even when life takes unexpected turns.

MARKET TRENDS

The market for trustworthy generative AI is flourishing, driven by these key trends.

1. Regulatory compliance: Increasing government regulations demand rigorous testing and transparency.
2. User awareness: Growing awareness among users regarding the importance of trustworthy and ethical AI systems.
3. Operationalization of ethical principles: Specialized consulting to guide AI developers in creating ethical risk mitigations on a technical level.

RESPONSIBLE USE OF GENERATIVE AI

Ethical considerations are at the heart of these groundbreaking achievements. The responsible use of generative AI ensures that while we delve into the boundless possibilities of artificial intelligence, we do so with respect for privacy and security. Ethical generative AI, exemplified by Försäkringskassan’s initiative, paves the way for a future where innovation and integrity coexist in harmony.

“ETHICAL GENERATIVE AI IS THE ART OF NURTURING MACHINES TO MIRROR NOT ONLY OUR INTELLECT BUT THE VERY ESSENCE OF OUR NOBLEST INTENTIONS AND TIMELESS VALUES.”

INNOVATION TAKEAWAYS

TRANSPARENCY AND ACCOUNTABILITY

Generative AI systems should be designed with transparency in mind. Developers and organizations should be open about the technology’s capabilities, limitations, and potential biases. Clear documentation and disclosure of the data sources, training methods, and algorithms used are essential.

BIAS MITIGATION

Generative AI models often inherit biases present in their training data. It’s crucial to actively work on identifying and mitigating these biases to ensure that AI-generated content does not perpetuate or amplify harmful stereotypes or discrimination.

USER CONSENT AND CONTROL

Users should have the ability to control and consent to the use of generative AI in their interactions. This includes clear opt-in/opt-out mechanisms. Respect for user preferences and privacy and data protection principles should also be upheld.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 7 features 16 such fascinating articles, crafted by leading experts from Capgemini, and partners like Aible, the Green Software Foundation, and Fivetran. Discover groundbreaking advancements in data-powered innovation, explore the broader applications of AI beyond language models, and learn how data and AI can contribute to creating a more sustainable planet and society.  Find all previous Waves here.

I am proud to announce our achievement of the AWS Generative AI Competency. This accomplishment marks a pivotal milestone on our decade-long journey with AWS.

Notably, we recently announced the signing of a multi-year strategic collaboration agreement with AWS, designed to accelerate the adoption of generative AI solutions and technologies amongst organizations of all sizes.

Alongside AWS, at the heart of our generative AI journey is the determination to help clients realize the full value of GenAI at scale, transforming their businesses to stay focused on a digital and sustainable economy. By leveraging Capgemini’s existing network of AWS Centers of Excellence, we can help clients realize value at speed, by accelerating the deployment of innovative industry-specific and functional use cases. These use cases are made possible by the AWS technologies of Amazon Bedrock to access a range of secure, high-performing Foundation [MC1] Models, including Amazon Titan.

What distinguishes Capgemini in the field of Generative AI?

In our recent Capgemini Research Institute report ‘Harnessing the value of Generative AI’,  74% of executives agreed the overall benefits of generative AI outweigh the associated risks. Our report guides organizations to focus on the following key areas to accelerate their generative AI journeys amid a rapidly evolving application landscape:

• Integrate genAI into the organization’s strategy and operations
• Drive a human-centered approach to scaling genAI
• Focus on sustainable development
• Build trust and responsibility in the AI systems
• Establish guidelines around usage

Our expertise in building the foundations for generative AI across all these key areas, empowers us to push boundaries for you, tackling even the most complex AI challenges. With an ongoing commitment to excellence through our AWS Centers of Excellence, we have a consistent measure of the latest training resources on AWS, the highest number of Generative AI badges, and a 10-year strong partnership enabling us to seamlessly work end-to-end as an integrated team. It means we can help organizations across all industries, achieve the best possible outcome.

The unique advantages of AWS Generative AI

AWS is renowned for its robust cloud technologies, setting a high bar for innovation and performance in the technology landscape. But what sets AWS Generative AI technologies specifically apart from the competition is their unparalleled scalability, security, and flexibility.

AWS provides a comprehensive suite of tools and services that empower developers to build, train, and deploy machine learning models more efficiently than ever before. AWS Generative AI technologies stand out particularly in the areas of:

• Extensive service suite: AWS offers a wide range of AI services, including Amazon SageMaker for building, training, and deploying machine learning models at scale, and AWS Lambda for running code without provisioning or managing servers, facilitating rapid deployment of AI applications.
• Unparalleled scalability and reliability: AWS’s infrastructure supports scalable AI applications, making it suitable for projects ranging from small-scale experiments to large-scale enterprise deployments.
• Customization at its core: AWS has been expanding its generative AI offerings, providing tools and services that allow for the easy integration of generative AI functionalities into applications, emphasizing customization and control.

Step into the future of AI with our proven expertise, and the leading technology of AWS

Together, we can help you explore how to:

• Integrate GenAI seamlessly into your operations. Streamline processes and personalize experiences.
• Drive sustainable innovation. Develop responsible, ethical AI solutions that can benefit both your business and the environment.
• Scale your AI journey with confidence. Leverage our industry-leading expertise and reputation. Find out more about our journey with AWS.

I invite you to connect with me today to explore the full potential of Generative AI.

Join us for this interesting and insightful conversation with, Marjorie Bordes, Vice President, Group Cyber Defense Operations, where she explains the importance of diversity in cybersecurity, how Capgemini’s values foster a positive and supportive work environment, and how she finds the cybersecurity profession both fascinating and fulfilling.

1. Tell us about your role. What does a day in your life at Capgemini look like? 

Every day is a new day depending on new rising threats, major attacks on the market and/or incidents impacting our clients that need the involvement of my Cyber Defense team. Part of my role is to enable and empower my teams to do what they do best: protect Capgemini against potential external and internal cyber threats. Together, we are facing daily complex situations to solve; we challenge each other on the best way to deal with them and adapt our posture in the context of constantly evolving threats. On top of that, I’m excited to contribute to our global digital transformation, demonstrating that cyber is not something that we need to be weighed down by, but part of the solution to accelerate a client’s business and secure their future.  

2. What makes you proud to work at Capgemini? 

I’m proud to work at Capgemini because everything is possible, as long as you have a good idea, you are able to put it into practice, develop it, and deliver it. This entrepreneurial spirit is really present and absolutely amazing. It allows us to be an active player in the future we want!

3. How are you working towards the future you want? 

By concentrating our efforts on the production of high-quality cyber threat intelligence which structures our threat detection capabilities, guides our offensive security programs, and helps our customers to adapt on a day-to-day basis their cybersecurity posture.   

4. What difference does it make to have diversity in the cyber leadership? (The value of diversity in the cyber leadership) 

Diversity is very key in cyber because it allows us to break down certainties, cross viewpoints, experiences, and sensitivities. It’s an undeniable asset for understanding the complexity of our business. I’m already looking forward to continuing to enrich our team with very different profiles and backgrounds, and I’m proud to start the journey to be able to welcome neurodiverse profiles very soon.  

5. What advice would you give to someone joining Capgemini Cybersecurity? 

Enjoy your new journey among a community of very skilled experts. Connect with the people all across the Globe, understand their respective missions and how you’ll work with them, and learn from all of them as well. You’ll discover how your uniqueness will serve/support the Capgemini One Team.

Finally, I never asked myself if I was able to do something or not because I’m a woman.  I have spent my career working in professional environments that historically have been dominated by male colleagues. I have never seen this as a barrier, I have always been driven by the skills and experience I can offer.  Being a woman has never stopped me at all.  

If you are looking for a role in cybersecurity at Capgemini, please visit our career page