Name: Deploying Sustainable AI Infrastructure
Start: 2024-01-25T16:00:00Z
End: 2024-01-25T16:00:28.000Z
Location: BrightTALK
Rating: 5

Data is the foundation of any organization and therefore, it is paramount that it is managed and maintained as a valuable resource. 

Subscribe to this channel to learn best practices and emerging trends in a variety of topics including data governance, analysis, quality management, warehousing, business intelligence, ERP, CRM, big data and more.

In the world of business analytics, technical accuracy does not equate business impact. Without the trust of leadership, even the most sophisticated analytics models fail to translate data into action. Data managers must recognize the critical gap is not in the data, but in the narrative they present. 

In this session, Google’s Jiaxi Zhu will introduce a four-part, narrative-driven analytics framework for bridging the divide between analytics and real-world business outcomes. 

Through in-depth examples, he will demonstrate how to:
- Design analytics models with action in mind.
- Frame outputs in a decision-ready context. 
- Shape complex insights into coherent, compelling stories that drive action.

From Insights to Impact: Building Narrative-Enabled Analytics to Drive Executive Decision-Making

The customer journey doesn't live in one department. It stretches across marketing, sales, finance, and support — and along the way, manual processes, disconnected tools, and slow handoffs create gaps that frustrate customers and weaken business performance. From invoices that go unpaid, to limited visibility into cash flow, to rising churn, enterprises are feeling the impact of these disconnects in tangible ways that affect the bottom line.

This session cuts through the GenAI hype to focus on practical, safe, and measurable implementation across end-to-end customer process flows. You'll discover methodologies for identifying which problems are worth solving first, how to integrate manual and digital steps into one intelligent workflow, and where human oversight remains essential to prevent costly mistakes. We'll also dig into real-world strategies for managing GenAI's inaccuracies — ensuring invoices are correct, forecasts are reliable, and customer interactions build trust instead of risk.

Join Eugina Jordan, CEO and Co-Founder, YOUnifiedAI, as she reveals proven approaches to GenAI implementation that deliver measurable business outcomes across critical enterprise functions.

- Identify high-ROI opportunities for GenAI implementation across three critical workflows: invoicing, cash flow management, and customer retention
- Implement effective human-in-the-loop protocols that mitigate GenAI hallucinations while maximizing automation benefits
- Design cross-functional workflows that eliminate departmental silos and create seamless customer experiences
- Develop practical metrics to measure GenAI's impact on revenue acceleration, operational efficiency, and customer satisfaction
- Apply a strategic framework for scaling successful GenAI implementations across your organization

Transforming the Customer Journey with GenAI Across the Enterprise

Support teams are at a critical inflection point, with GenAI reshaping customer expectations overnight. While automation promises efficiency, it often creates impersonal experiences that damage loyalty. The most successful organizations are discovering that GenAI's true power lies not in replacing human interactions, but in strategically enhancing them at every touchpoint.

Generative AI offers transformative potential for support experiences, but only when implemented with a human-centered approach. This session defines GenAI specifically within the support context and explores practical applications that benefit both end-users and support agents. You'll discover how intelligent automation can scale operations while simultaneously improving satisfaction metrics across your support ecosystem.

Join Phyllis Drucker (Influencer, EZ2BGR8 Service Management) to explore proven frameworks for implementing GenAI solutions that put people first while driving measurable business outcomes.

Key Takeaways:

- Find the right balance between scaling support operations and maintaining customer satisfaction
- Implement GenAI-powered chatbots that deliver near-human experiences through contextual understanding
- Create customized, tailored responses that increase satisfaction and engagement 
- Establish measurement systems that quantify GenAI's impact and inform future initiatives
Develop a practical roadmap for implementing GenAI in support functions, regardless of your starting point

Human-Centered GenAI Support: Winning Customer Loyalty in the Automation Era

Despite massive investment and executive enthusiasm, most organizations implementing GenAI remain stuck in perpetual pilot purgatory. Behind the headlines and hype, a select group of companies has quietly crossed the chasm from experimentation to enterprise-wide transformation—achieving what their competitors merely discuss in boardrooms. Their secret isn't better technology, but rather a systematic approach to implementation that balances ambition with pragmatism.

GenAI's true power lies in enterprise-wide applications—reimagining customer experiences, supercharging product innovation cycles and transforming operational efficiency across every business function. The question isn't whether to implement GenAI, but how quickly you can transition from experimentation to organization-wide transformation while balancing innovation with responsible governance and ethical considerations.

Join Pankul Chitrav (Application Release Engineer, TD Bank) to discover how your organization can build an actionable GenAI roadmap that delivers immediate business impact while positioning you for sustainable competitive advantage.

Key Takeaways:

- Explore how leading organizations are applying GenAI to create tangible business value across functions
- Learn specific strategies to expedite product development, content creation, and decision-making through GenAI implementation
- Master techniques for streamlining operations while delivering hyper-personalized services at scale
- Gain actionable insights on governance frameworks, ethical considerations, and sustainable GenAI adoption strategies

Unleashing Generative AI: Transform Business Strategy from Concept to Competitive Edge

With AI tools exploding, organizations today are bombarded with new technical tutorials and prompt engineering tactics. But they often become obsolete within weeks. While competitors chase fleeting GenAI techniques, the true competitive advantage lies not in mastering specific tools, but in cultivating something far more fundamental. This presentation reveals the missing catalyst that transforms GenAI from a specialized technology into an organization-wide force multiplier.

The challenge isn't in teaching your teams how to use GenAI—they're already adopting it in their personal lives. It's in creating an environment where innovation flourishes organically across all levels of your organization. Brian Kirsch demonstrates why empowering employees to apply their unique job expertise to GenAI implementation delivers more sustainable results than top-down technical approaches. Learn how to establish the right framework that enables continuous innovation without requiring constant retraining as the technology evolves.

Join Brian Kirsch, IT Instructor and Industry Expert, to discover the one evergreen principle that drives successful GenAI adoption across organizations of all sizes.

Key Takeaways:

- Understand why traditional GenAI implementation approaches fail to deliver lasting competitive advantage
- Learn to empower employees at all levels to become drivers of AI innovation without technical expertise
- Discover a sustainable framework for GenAI adoption that remains effective despite rapid technological changes
- Gain practical strategies for fostering an environment where AI-driven innovation flourishes organically
- See real-world examples of how simple ideas can create profound change across departments

Unlocking the Secret to Sustained Innovation with GenAI

Generative AI is rapidly transforming collaboration by enabling capabilities such as summarization, workflow automation, translation and more. Generative AI offers the potential to fundamentally transform how teams and individuals collaborate and create, eliminating mundane activities and fostering innovation.

In this session, we’ll explore how Generative AI is changing the workplace collaboration landscape, including availability of tools within collaboration applications, third-party tools, and studios enabling custom AI tool creation. We’ll look at organizational strategies and share real-world examples of approaches that achieve measurable success. We’ll also look at security, compliance, and governance concerns to minimize risk.

Key Takeaways:

- Learn how to identify and implement the right Generative AI tools for your team's specific needs, whether that means using built-in features in existing applications, integrating third-party solutions, or building custom tools for unique workflows.
- Understand how to create a foundational strategy for introducing Generative AI into your organization, including understanding which collaborative tasks can be automated to free up time for strategic work.
- Gain knowledge to evaluate and address security, compliance, and governance risks associated with Generative AI, enabling you to implement these tools responsibly and minimize potential liabilities.
- Discover how to measure the success of Generative AI initiatives by measuring before and after improvements resulting from implementation.

Leveraging Generative AI to Improve Collaboration

Storytelling is one of humanity's oldest tools—yet in the corporate world, its power remains largely untapped. Every day, brilliant business ideas die silently, buried beneath technical specifications and corporate jargon. The result? Missed opportunities, disengaged stakeholders, and strategies that never reach their potential. What if you could break this cycle and transform how your ideas are received and implemented?

With GenAI, business leaders can go from dense and technical business language to persuasive narratives that connect and convert. By leveraging AI-powered storytelling techniques, operations leaders, IT professionals and transformation executives can overcome the traditional disconnect between technical teams and business decision-makers, creating alignment that accelerates adoption and drives measurable outcomes. For professionals working in enterprise processes, AI operations, and digital transformation, this capability isn't just nice-to-have—it's essential for ensuring your initiatives receive the right support and resources.

In this session, Inigo Antolin (Head of Data Management and Governance at The British Council) reveals how to harness GenAI to transform your business communication from forgettable presentations into strategic narratives that drive action and results.

Key Takeaways

- How the storytelling gap is undermining enterprise process improvements and technology adoption in data-driven organizations
- Practical frameworks for using GenAI to translate complex technical concepts into compelling business narratives
- Techniques to customize your storytelling approach for different stakeholders across the enterprise
- Ready-to-implement GenAI tools and prompts that enhance communication effectiveness without requiring creative expertise
- Measurable business outcomes achieved by organizations that have mastered GenAI-powered storytelling in process transformation initiatives

GenAI Storytelling: Turning Technical Complexity into Business Impact

Customer retention has never been more important - or challenging. With rising acquisition costs, keeping the customers you already have is paramount, but they're constantly bombarded with competing offers. The key to standing out and fostering loyalty lies in delivering personalized experiences that make them feel valued and understood. Are you truly leveraging your customer data to create these stickier relationships?

The surge of customer data coupled with fragmented digital touchpoints presents a complex challenge. Many companies are overwhelmed - struggling to translate raw data into actionable insights and personalised experiences that resonate with individual customers. Traditional marketing tactics fall short, leading to missed opportunities to build lasting relationships, drive loyalty, and achieve sustainable growth. This is precisely why embracing a connected customer strategy has never been more critical.

Join Anna Samkova, Co-Founder & Strategic Advisor at Albany Advisory, for this session to explore how to unlock exponential growth by turning customer data into personalized experiences with the C.L.I.E.N.T. Growth Framework.

Key Takeaways:

- Implement the C.L.I.E.N.T. Growth Framework to transform raw customer data into a powerful engine for personalization
- Discover proven strategies to activate data in ways that feel personal, purposeful, and commercial
- Gain actionable insights into what truly meaningful personalization looks like in 2025 and beyond – and how to deliver it effectively
- Identify and avoid common personalization pitfalls that can damage customer trust and undermine your ROI
- Understand how to build a connected customer strategy that drives customer lifetime value, loyalty, and sustainable revenue growth

The C.L.I.E.N.T. Growth Framework: Your Roadmap to Personalized CX Success

Sustainability has become a defining element of modern customer experience (CX), shaping how companies build trust, deliver value and foster long-term relationships. Today’s stakeholders expect more than responsiveness and services; they want transparency, environmental accountability and data-driven insights.  

CHEP's transformation from traditional platform provider to data-driven sustainability partner illustrates how organizations can turn environmental commitments into competitive advantages. By embedding circular economy principles into customer touchpoints, companies create dual value: reducing environmental impact while enhancing customer relationships through transparency, efficiency and shared purpose. This approach transforms sustainability from a compliance exercise into a powerful engine for customer loyalty and operational excellence.

Hear from CHEP leaders on how sustainability is reshaping customer experience expectations across industries.

Key Takeaways:

- Insights for embedding sustainability metrics and circular innovation across customer touchpoints 
- How transparent environmental reporting strengthens customer relationships and reduces friction points
- Techniques for leveraging digital systems to enable circular business models and quantify sustainability impact
- Methods for integrating self-service platforms with predictive analytics to deliver more sustainable, responsive service

Accelerate Loyalty Through Circular Innovation in Today's Sustainability Market

Customer conversations contain strategic revelations that most executives never hear, yet these unfiltered moments often predict market shifts before formal data ever could. Although 84% of CX leaders advocate for bringing these insights to the executive table, many organizations still treat customer interactions as operational noise rather than the strategic signal they actually represent. 

Although 48% of companies now employ interaction analytics, many struggle to effectively distribute these insights beyond the contact center. Additional advantages come fromsystematically analyzing customer interactions to inform product development, marketing strategies, and executive decisions; creating a unified approach to customer experience that drives measurable business outcomes and strengthens customer loyalty across the entire journey. 

Join Robin Gareiss, CEO of Metrigy, as she shares research-backed strategies that transform conversation data into business value. 

Key Takeaways: 

- Discover which conversation metrics deliver the most substantial business intelligence and how to capture them effectively 
- Learn practical frameworks for distributing interaction insights across departments to create organization-wide customer-centricity 
- Understand how to quantify the ROI of conversation intelligence through improved business metrics and enhanced customer satisfaction 
- Gain actionable implementation strategies that work regardless of your current analytics maturity

Conversation Intelligence: The Hidden Gems that Impact all Business Decisions

Your customer just spent 15 minutes navigating your support portal only to end up exactly where they didn't want to be: on hold with your call center. This all-too-common scenario reveals the main flaw in how organizations approach digital self-service: designing for scale rather than CX success. 

Unfortunately, customer portals are often designed primarily to eliminate contact via more costly resources. When designed solely to scale support, they fail to meet the CX mark. The best portals humanize the digital experience by understanding the customer's journey and anticipating needs before frustration sets in.

This session examines the critical need to balance operational efficiency with customer-centered design principles that transform portals from necessary evils into preferred channels.

Join Phllis Drucker (Influencer, EZ2BGR8 Service Management) to explore how to achieve great CX results through innovative portal design that puts customers first while still delivering operational benefits.

Key Takeaways:

- Identify common pitfalls that typical portals fall into and how to avoid them
- Apply customer journey mapping techniques to create intuitive, emotionally intelligent digital experiences
- Implement a practical roadmap for designing and innovating a new portal experience
- Measure the true ROI of your portal beyond call deflection metrics
- Balance automation with human touchpoints to create meaningful digital interactions

Humanizing Digital Portals: Transform Self-Service in the Age of CX Expectations

The AI implementation paradox haunts contact centers everywhere. With sophisticated technologies being deployed and substantial investments made, the promised revolution in efficiency and experience remains frustratingly slow. This disconnect between expectation and reality has left many CX leaders questioning whether their AI strategy has missed the mark.

The challenge lies not in the technology itself, but in how it's implemented and aligned with broader business objectives. As contact centers evolve into multi-channel customer engagement hubs, simply layering AI onto existing processes isn't enough. Success requires thoughtful integration that considers both customer and employee perspectives, proper design principles and strategic alignment with business goals.

Join Catriona Howell, CX Consultant, for an insightful case study exploration that reveals how to bridge the gap between AI implementation and meaningful business outcomes in the modern contact center.

Key Takeaways:

- Identify common pitfalls that prevent AI and automation from delivering expected results in contact center environments
- Discover practical strategies for aligning technology implementation with both customer and employee experience goals
- Learn how to design AI solutions that enhance rather than hinder the human elements of customer service
- Understand how properly implemented contact center AI can generate broader business value through customer insights and engagement

Beyond Automation: Unlocking Real Value from AI in the Contact Centre

The AI implementation paradox haunts contact centers everywhere. With sophisticated technologies being deployed and substantial investments made, the promised revolution in efficiency and experience remains frustratingly slow. This disconnect between expectation and reality has left many CX leaders questioning whether their AI strategy has missed the mark.

 

The challenge lies not in the technology itself, but in how it's implemented and aligned with broader business objectives. As contact centers evolve into multi-channel customer engagement hubs, simply layering AI onto existing processes isn't enough. Success requires thoughtful integration that considers both customer and employee perspectives, proper design principles and strategic alignment with business goals.

 

Join Catriona Howell, CX Consultant, for an insightful case study exploration that reveals how to bridge the gap between AI implementation and meaningful business outcomes in the modern contact center.

 

Key Takeaways:

 

Identify common pitfalls that prevent AI and automation from delivering expected results in contact center environments
Discover practical strategies for aligning technology implementation with both customer and employee experience goals
Learn how to design AI solutions that enhance rather than hinder the human elements of customer service
Understand how properly implemented contact center AI can generate broader business value through customer insights and engagement

Beyond Automation: Unlocking Real Value from AI in the Contact Center

Small and medium enterprises are drowning in data while starving for insights. With unstructured data projected to represent up to 90% of all enterprise data by late 2025, and only 35% of SMEs leveraging cloud-based analytics, there's an enormous untapped potential for competitive advantage. In today's AI-driven landscape, the ability to transform raw data into actionable intelligence isn't just beneficial—it's essential for survival and growth.

While large enterprises deploy specialized teams and substantial budgets to tackle data challenges, SMEs face unique obstacles in extracting value from their information assets. Without proper frameworks for data cleansing, integration, and governance, organizations risk making critical decisions based on flawed insights. This session delivers practical, cost-effective strategies specifically designed for businesses without enterprise-scale resources, helping you navigate regional compliance variations and integrate data across disparate systems to drive measurable ROI.

Join Eugina Jordan (CEO and Co-founder of YOUnifiedAI) to explore proven methods for converting data chaos into strategic advantage.

Key Takeaways:
- Practical frameworks for effectively managing both structured and unstructured data sources
- Step-by-step methods for ensuring data quality and integrity across your organization
- Integration strategies that bridge legacy systems with modern platforms without breaking the budget
- Governance approaches that address regional compliance variations while maintaining data accessibility
- Real-world examples of SMEs that have successfully converted disparate data into revenue-driving insights

From Data Chaos to ROI: Practical Frameworks for SMEs

The way employees communicate and collaborate is constantly evolving, and so too are the security threats they face. The rise of generative AI adds a new layer of complexity, requiring CISOs to proactively address the risks of data loss and potential harm to the organization.

Traditional security approaches often fall short in addressing the unique challenges posed by modern collaboration tools and the integration of GenAI. Understanding and mitigating these risks is critical for maintaining data privacy, preventing leakage, and ensuring compliance. We'll share Metrigy's latest research data to reveal actionable strategies for a comprehensive, business-aligned security strategy.

Join Irwin Lazar (President and Principal Analyst at Metrigy)  to discover the key components of a modern security approach, including how to: 

- Establish alignment between IT, collaboration, and security teams to address evolving threats.
- Identify emerging threats stemming from new applications and out-of-band communications.
- Understand how generative AI creates new risks for data privacy, leakage, and effective data management.
- Develop a comprehensive security strategy tailored for collaborative environments and the GenAI landscape.
- Evaluate the benefits of third-party platforms optimized for collaboration and GenAI security to enhance your security posture.

Secure Collaboration in the Age of GenAI: A CISO's Guide to Risk Mitigation

Sustainable business relationships center on both long-term collaboration and minimizing environmental impact throughout the supply chain. Effective manufacturing and supply chain processes are increasingly reliant on transparency, adaptability, and digital tools that allow for predictive, rather than reactive, planning.

This session presented by CEO Justin Newell will demonstrate -- using a few examples -- how organizations such as Volkswagen have leveraged generative AI and intelligent decision-making systems to enhance sustainability and efficiency within logistics, supply chain, and manufacturing. 

AI is most powerful when it processes dozens or even hundreds of factors simultaneously -- far beyond the capacity of human decision-making or traditional systems. AI-driven optimization engines allow companies to simulate countless supply chain scenarios in real time, identifying the most sustainable and efficient outcomes.

When manufacturing and logistics processes are optimized through AI, delays are minimized, expectations are met more consistently, and customer satisfaction rises due to great transparency and on time delivery performance. The transparency and speed that come from real-time data and predictive analytics foster trust and reliability -- both cornerstones of sustainable business relationships.  Solutions such as this not only reduce operational complexity but also help reach environmental and service quality goals more effectively.
This can lead to more sustainable business relationships — both in longevity and from an environmental impact -- and increased customer satisfaction. 

Key Takeaways 
1. Trends in AI for 2025 and 2026.
2. Real-world examples of AI/ML in action.
3. How complex logistics can be better managed with AI and digital decision making.
4. Innovative solutions to improve manufacturing operations and product lead times with AI.

Reshaping the Role and Impact of AI in Manufacturing and Supply Chain Logistics

In the era of zettabyte scale information, organizations often find themselves “data rich but insight poor.” While data volume has exploded, the ability to translate that data into competitive advantage lags behind. The consequence? Missed opportunities, inefficient operations, and a failure to capitalize on the full potential of today's technology.

But technology alone is not enough. True scalability demands a people‑first culture that champions collaboration, shared data definitions, and continuous learning. By aligning technical choices with clear business goals and fostering an environment where data informs every decision, companies can bridge the gap between big data and big insights - moving from dashboards that describe the past to systems that actively shape the future.

In this session, we delve into the challenges preventing organizations from maximizing their data investments. We explore how to bridge the gap between raw data and strategic insights by building scalable, purpose-built systems that leverage cutting-edge technologies like AI and machine learning. Discover practical approaches to data integration, governance, and analytics that empower your teams to make data-driven decisions, optimize processes, and unlock new revenue streams.

Join Dmytro Basan to discover how to turn your data into a strategic weapon.

Key takeaways:

- Define Clear Business Objectives: Align your data strategy with business goals to ensure a measurable ROI.
- Build a Scalable Data Foundation: Invest in a modern data architecture that can handle growing data volumes and diverse data sources.
- Embrace Automation and AI: Leverage AI-powered analytics to automate insights discovery and accelerate decision-making.
- Promote Data Literacy: Empower your employees with the skills and tools they need to access, analyze, and interpret data effectively.
- Measure and Iterate: Continuously monitor the performance of your data initiatives and adjust your strategy based on results.

Unlocking Data's Potential: Scaling Systems for Real Insights

The marketplace is buzzing with AI expectations, but where's the real business value? Despite massive investment and executive enthusiasm, most organizations remain stuck in the perpetual pilot phase, unable to translate AI potential into tangible outcomes that impact the bottom line.

Data volumes continue to expand at unprecedented rates. Meanwhile, regulatory requirements grow increasingly complex. These dual pressures demand that enterprises extract meaningful intelligence from their data assets while maintaining strict governance protocols. Practical AI implementation has become essential for survival, not just competitive advantage.

Moving from AI aspiration to implementation requires many critical decisions.
When is building in-house capabilities the right choice, and when is it best to go with third-party providers? How can you use the analytical power of AI while protecting sensitive data? And at what points does human expertise remain irreplaceable in your AI strategy?

Join TreeHive Strategy Principal, Donald Farmer as he delivers actionable strategies for enterprise leaders navigating real-world AI deployment challenges.

Key Takeaways:

- Practical decision frameworks for evaluating build-versus-buy AI strategies that align with your organization's data maturity and business objectives
- Governance approaches that protect proprietary data while maximizing AI's analytical potential across your enterprise
- Strategies for managing integration complexity when deploying AI within existing data management infrastructures
- Methods for identifying where human expertise remains critical in your AI-augmented data operations
- Actionable roadmap for scaling successful AI pilots into enterprise-wide data management solutions

AI That Works: Strategic Implementation for Measurable Business Outcomes

Generative AI has the potential to revolutionize businesses by adding over $4 trillion to the global economy. This figure could even double if the impact of embedding generative AI into software is considered. To maximize this opportunity, businesses need to move from proofs of concept (POCs) to production quickly and cost-effectively. This requires integrating generative AI into decision-making processes and establishing a trusted AI ecosystem. By doing so, businesses can gain accurate and actionable insights that deliver value both now and in the future.

Join Vedat Akgun, Ph.D., VP of Data Science & AI at Teradata and Wayne Eckerson, President, Eckerson Group as they discuss how organizations can deliver trusted AI innovation at scale.

Three Steps to Creating Enterprise Value with Generative AI

Knowledge is power. If you want to get more from modern data, Pure’s Tech Talk series can supercharge your storage savvy. Led by Pure solution experts and industry guests, these lively discussions explore features, live demos, and best practices to address the use cases you care most about. You’ll come away informed, inspired—and ready to unleash the full power of modern data for your business. Uncomplicated Data Storage, Forever.

While commercial AI offerings have existed for over 50 years, 2023 is shaping up to be a breakout year as enterprises and businesses of all sizes invest in AI to advance their goals. AI advances including creative and generative AI, AI-human collaboration, low or no-code AI are just the tip of the iceberg.

Join Dr. Kirk Borne, an acclaimed data scientist and AI expert, and a panel of Pure Storage AI experts in this exciting discussion on what’s HOT in AI today, opportunities with AI in the future, and lessons learned from our expert panel on small to massive AI initiatives that they’ve each had hands-on experience with.

Additional topics include:
* Optimizing outcomes with infra/storage architected for AI
* Aligning goals between data/AI/analytics teams with IT/Infra teams for optimal AI (AI Centers of Excellence)
* Meeting ESG goals associated with AI projects
* Top Impacts to AI with the right storage platform
* Consolidation of app data and the benefits of that

Future of AI & Lessons Learned from a Former Space Scientist, now Data Scientist

Enterprise Strategy Group Distinguished Analyst Jon Oltsik Presents: 

From skills shortages to nuanced cyber-attacks, cybersecurity leaders have well-documented challenges that threaten the successful protection of their business. Generative artificial intelligence (GenAI) has burst onto the scene promising a long list of potential applications, with cybersecurity improvement touted among them. This session will explore cybersecurity use cases, including those employed by Security Operations Analyst for threat detection and response purposes.

Cybersecurity GenAI Use Cases

In the era of digital transformation, the ability to access and harness the vast sea of information within an enterprise is crucial. Join us for a concise yet impactful 20-minute webinar where we'll explore a game-changing solution: bringing a large language model behind your firewall to revolutionize enterprise content search. 

Key Highlights: 

The Age of Large Language Models: Discover why large language models have become a cornerstone of modern AI and how they can transform content search within your organization. 

The Security Advantage: Explore the benefits of hosting a language model within your own infrastructure, ensuring the utmost data security and compliance. 

Tailored to Your Needs: Learn how to customize and fine-tune the language model to cater specifically to your enterprise's unique content search requirements. 

Enhancing Efficiency: Uncover how leveraging a large language model can significantly boost your content search efficiency, allowing you to extract insights and make data-driven decisions faster than ever. 

Join us for this enlightening session and equip yourself with the knowledge and strategies to bring a large language model behind your firewall, empowering your organization to navigate the digital landscape with confidence and precision.

Maximizing Enterprise Content Search with Generative AI

Join us for an insightful fireside chat as we peer into the future of artificial intelligence (AI) in 2024. In this dynamic session, industry experts will share their predictions and unveil the vast opportunities ahead in the rapidly evolving landscape of AI. Our speakers will delve into key areas shaping the AI ecosystem, exploring recent advancements in machine learning, large language models (LLMs), and beyond. Studying transformative breakthroughs to emerging trends, we will analyze the forces propelling AI innovation and their potential impact on industries ranging from healthcare and finance to manufacturing and entertainment.

In this webinar, you will learn:

What could be next, after this year’s explosive growth of large language models (LLMs)
Strategic considerations for organizations and data professionals navigating the AI landscape in 2024
How open-source AI and closed-source AI will compete in the coming year and the potential outcomes of the race to build marketable AI systems

AI in 2024: Unveiling Predictions and Seizing Opportunities

Data is the new oil, but raw data is not valuable. It needs to be cleaned and augmented to be useful. 
While everyone wants to get the most out of their data with AI, it can be slow and painful to prepare the data, train your models, and create checkpoints at scale. 

This requires new technologies and collaboration between teams to go from raw data to business outcomes. 

Join Markus Grau, JB Thomas, and Michael Kaspers to hear about their first-hand experience tackling these challenges.
You might be surprised where storage can enable your AI journey.

Boost Your AI Initiatives from Ingest to Inference in a Flash

Enterprise Strategy Group Principal Analyst Mike Leone Presents: 

Application developers are challenged with efficiently creating innovative solutions while managing time constraints, which can be mitigated by the transformative impacts of generative artificial intelligence (AI) streamlining code generation and accelerating development processes. Organizations have integrated generative AI (GenAI) into their operational setup to accelerate code creation, refine code structures, elevate code quality, and deliver personalized customer experiences. By harnessing GenAI, application developers tackle issues by capitalizing on the technology’s ability to automate tasks, drive creativity, and deliver innovative solutions.

The Role of GenAI in Application Development

With so many people – like your CIO – hyped about artificial intelligence, machine learning, and generative AI products like ChatGPT, you’re likely under a lot of pressure to develop applications with those technologies for your company.

Like, yesterday.

But how do you turn terabytes of unstructured data – ranging from text to images, audio, and video – into useful information for the AI application?

The answer is a vector database. Vectorizing converts unstructured data into numerical representations known as vector embeddings, and Redis stores, indexes, and retrieves them. Vectors make searching for similar images or text or documents – vector similarity search (VSS) – faster and easier. Moreover, an external vector database with domain-specific, proprietary, or more recent data – used with public general purpose large language models – improves AI application responses.

Not to mention, keeping it from making things up.  
In this tech talk, find out how to use Redis’s vector database capabilities for real-time AI apps. We show the elements of building generative AI applications – using Redis technology you already know.

Watch to find out more about it.
* What’s a vector database
* Examples
* Why LLMs need real-time response
* Redis Enterprise VSS features and differentiators

Driving AI Innovation: Making It Easy to Build Generative AI Apps with Redis

Enterprise Strategy Group Principal Analyst Mike Leone Presents:

The larger and more accurate the data set, the more effective the AI model. However, the road leading to that seemingly simple goal is strewn with roadblocks that pose substantial challenges for many organizations. Data experts and data quality tools and techniques to ensure the quality and accuracy of collected data while also assuring data is compliant with industry regulations is critical. This session will explore these considerations as well as how moving huge data sets to AI is also subject to service level agreements.

AI Data Quality, Compliance, and Infrastructure Requirements

For decades, organizations have sought to improve leadership and decision-making through data-driven capabilities that synthesized information and delivered insights. Now, generative AI has unlocked new opportunities for organizations to increase productivity, innovate faster, and outpace the competition.

To better understand how organizations can lead in the era of generative AI, Teradata and IDC surveyed 900 organizations across the globe, focusing on CDOs, CIOs, and CFOs. We found that there are leaders and laggards when it came to AI-driven decision-making—and that had a massive impact on market share, profitability, customer satisfaction, and employee satisfaction.
 
In this special event, join Teradata and guest speakers from IDC to discover:
• What separates AI leaders and laggards and how it impacts business outcomes
• How organizational culture and structure can accelerate AI value
• The technology that unleashes innovation for AI leaders

Speakers include:
• Dan Vesset – Group Vice President, Analytics and Information Management at IDC
• Chandana Gopal – Research Director, Future of Intelligence at IDC
• Chris Twogood – Senior Vice President of Product Marketing at Teradata
• Vedat Akgun, Ph.D. – Vice President of Data Science & AI at Teradata

Leadership and Decision-Making in the Era of Generative AI

Enterprise Strategy Group: GenAI Summit​

Enterprise Strategy Group Senior Analyst Jonathan Brown Presents: 

A common criticism of AI is its high potential to increase carbon footprints due to its heavy compute requirements. As a result, sustainability has risen to become a critical consideration for nearly all organizations. This session will explore how organizes balance deploying AI-ready infrastructure with well-defined sustainability requirements and the metrics designed to monitor energy-intensive AI environments.

Deploying Sustainable AI Infrastructure

Generative AI

Infrastructure

GenAI

Artificial Intelligence

AI Infrastructure

Sustainable AI

AIOps

Enterprise applications have become a crucial piece of infrastructure for many businesses. The enterprise applications community on BrightTALK features the latest insights in enterprise application integration, enterprise application architecture and EAS software. Join the community to gain access to thousands of videos and webinars presented by recognized enterprise information systems experts and arm yourself with the knowledge you need to succeed.

Enterprise Applications

Practicing business intelligence allows your company to transform raw data into sets of insights for targeted business growth. The business intelligence and analytics community on BrightTALK is made up of thousands of data scientists, database administrators, business analysts and other data professionals. Find relevant webinars and videos on business analytics, business intelligence, data analysis and more presented by recognized thought leaders. Join the conversation by participating in live webinars and round table discussions.

Business Intelligence and Analytics

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Big Data and Data Management

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Deploying Sustainable AI Infrastructure

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Business Intelligence and Analytics