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“Before starting a new AI project, it is really worthwhile defining the business priority first,” asserts Joanna Hodgson, the UK and Ireland regional leader at Red Hat.
“What specific problem are you trying to solve with AI? Do we need a general purpose AI application or would a more focused model be better? How will we manage security, compliance and governance of that model? This process can help to reveal where AI adoption makes sense and where it doesn't," she added.
In this episode of the Tech Transformed podcast, host Shubhangi Dua, podcast producer at EM360Tech speaks with Hodgson, a seasoned business and technical leader with over 25 years of experience at IBM and Red Hat. They talk about the challenges of scaling AI projects, the importance of open source in compliance with GDPR, and the geopolitical aspects of AI innovation.
They also discuss the role of small language models (SLMs) in enterprise applications and the collaboration between IBM and Red Hat in advancing AI technology. Joanna emphasises the need for a strategic approach to AI and the importance of data quality for sustainable business practices. While large language models (LLMs) dominate headlines, SLMs offer a cost-effective and efficient alternative for specific tasks.
The podcast answers key questions, like ‘how do businesses balance ethical considerations, moral obligations, and even patriotism with the drive for AI advancement?’ Hodgson shares her perspective on how open source can facilitate this balance, ensuring AI works for everyone, not just those with the deepest pockets.
Hodgson also provides her vision on the future of AI. It comprises interconnected small AI models, agentic AI, and a world where AI frees up teams to create personal connections and exceptional customer experiences.
TakeawaysCuriosity is a strength in technology.AI is becoming embedded in existing applications.Regulatory compliance is crucial for AI systems.Open source can enhance trust and transparency.Small language models are efficient for specific tasks.AI should free teams to create personal connections.A strategic AI platform is essential for businesses.Data quality is key for sustainable business success.Collaboration in open source accelerates innovation.AI can be used for both good and bad outcomes.
Chapters00:00 Introduction to the Tech Transform Podcast
01:35 Pivotal Moments in Joanna's Career
05:12 Challenges in Scaling AI Projects
09:15 Open Source and GDPR Compliance
13:11 Regulatory Compliance and Data Security
17:30 Geopolitical Aspects of AI Innovation
22:31 Collaboration Between IBM and Red Hat
23:58 Understanding Small Language Models
29:54 Future Trends in AI and Sustainability
About Red HatRed Hat is a leading provider of enterprise open source solutions, using a community-powered approach to deliver high-performing Linux, hybrid cloud, edge, and Kubernetes technologies. The company is known for Enterprise Linux.
They offer a wide range of hybrid cloud platforms and open source...
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Takeaways
#Satellitecommunications are essential for remote field teams.They provide safety and tracking for workers in isolated areas.Disaster preparedness involves proactive planning and communication.User-friendly #technology is crucial for effective utilisation.Reliable communication impacts day-to-day operations positively.Employers show care for employee safety through #satellitetechnology investment.Summary
In this episode of #TechTransformed, Jonathan Care discusses the importance of satellite communications for field teams. He is joined by Mark O'Connell, EMEA & Asia Pacific General Manager at Globalstar, and Grace Finn, Senior Account Manager at Peoplesafe. Together, they explore how satellite technology enhances safety, disaster preparedness, and operational efficiency for remote, lone workers.
We learn the differences between satellite and cell communication. O’Connell emphasises the importance of satellite communication, stating that due to field workers, there is a requirement to not be reliant on cellphone towers.
O’Connell further clarifies that field teams who are working remotely, and are away from terrestrial communications, need access to constant communication.
Finn also expresses the importance of field worker safety, sharing: “If the unforeseen does happen, they’re protected.” She emphasises that organisations should invest in satellite communications to ensure their teams' wellbeing and security.
Tune in to learn the user-friendly aspects of the technology, its features for challenging environments, and the critical role it plays in ensuring reliable communication.
For the latest tech insights visit: EM360Tech.com
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"Having the insight and being able to stitch together your technical resources and business decisions together, is the prime place where observability can add value to you,” stated Manesh Tailor, EMEA Field CTO at New Relic.
In this episode of the Tech Transformed podcast, Kevin Petrie, Vice President of Research at BARC, speaks with Manesh Tailor about the intersection of artificial intelligence (AI) and observability, and how this is positively changing business operations.
Tailor emphasises how intelligent observability has changed beyond simple monitoring to provide real-time insights into customer experience and the entire technology stack. This enables informed decisions across engineering, operations, and business domains, directly linking technical performance to strategic business outcomes.
He also discusses the different stages observability has been through and where it's leading to now. The current wave, Observability 3.0, takes advantage of AI to predict issues and even enable self-healing systems.
New Relic has embraced this two-way street, using AI within its platform. This was in an ambition to help users and "AI monitoring" to track the performance of language models alongside traditional metrics. Such a platform provides a holistic view of system health and the cost implications of AI deployments.
Alluding to the management of AI-powered applications, Tailor says collaboration is key between application and data science teams. Not only does it provide real time data but as a result leads to efficient decision making.
Futuristically, the speedy proliferation of AI agents has both pros and cons for observability. This is where New Relic comes in. It addresses the challenges by constructing a platform-centric "AI orchestrator" with a growing library of AI-native agents.
In essence, as AI-powered applications become increasingly integral to business operations, intelligent observability is no longer optional.
TakeawaysObservability is crucial for understanding unknowns in systems.AI enhances observability by providing predictive insights.The evolution of observability includes intelligent monitoring.Collaboration between technical and business teams is essential.Cost efficiency is a key focus in modern observability.Real-time data is vital for effective decision-making.Self-healing systems represent the future of observability.AI and observability must work in tandem for success.The complexity of systems is increasing, requiring better tools.Observability is applicable across all organizational levels.
Chapters00:00 Introduction to AI and Observability
03:10 Defining Observability and Its Evolution
05:49 The Role of AI in Observability
08:46 Navigating AI-Driven Applications
11:52 Target Users and Community for Observability
14:57 Collaboration Across Teams
17:55 Challenges and Opportunities in Observability
20:47 The Future of Observability and AI
23:54 Key Takeaways for CIOs and IT Leaders
About New RelicThe New Relic Intelligent Observability Platform empowers businesses to proactively eliminate disruptions in their digital experiences. As the only AI-enhanced platform that unifies and correlates telemetry data, New...
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Takeaways
#AIagents are #autonomous entities that can perceive and act.Human oversight is essential in the initial stages of AI implementation.Data quality and trust are critical for effective AI agents.Guardrails must be integrated into the design of AI agents.Modularity in design allows for flexibility and adaptability.#AI should be embedded in data management processes.Collaboration between data and application teams is vital.Summary
In this episode of #TechTransformed, Kevin Petrie, VP of Research at BARC, and Ann Maya, EMEA CTO at Boomi, discuss the transformative potential of AI agents and intelligent automation in business. They explore the definition of agents, their role in automating processes, and the importance of human oversight.
Maya introduces us into the world of AI agents stating that, at its core, it’s an autonomous entity within #AIsystems that can perceive its environment. This creates a deep dive into how they evolved from traditional automation to “observe, think, and act” in novel and autonomous ways.
Maya addresses AI skepticism by acknowledging its growing autonomy while underscoring the current necessity of human oversight. She also highlights data's crucial influence on an agent's perception and decisions, emphasising the need for quality, trustworthy data in effective AI.
Moreover, Maya and Petrie explore AI's practical implications, pointing to Google's agent-to-agent protocol as vital for managing language model interactions and enabling effective communication across diverse agents within complex systems.
For the latest tech insights visit: EM360Tech.com
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"If AI has proven anything, it will change pretty rapidly. Understanding its limitations and not asking too much of it is significant. What’s successful is prototyping tools," said Rob Whiteley, CEO of Coder. "Such tools where AI can create an application, while not the world's most graceful code but will get you to working prototype pretty quickly. That would probably take me days or weeks of research as a developer, but now I have a working prototype so I can socialise it."
In this episode of the Tech Transformed podcast, Dana Gardner, a thought leader, speaks with Rob Whiteley, CEO of Coder, about the transformative impact of agentic AI on software development. They discuss how AI is changing the roles of developers, the cultural shifts required in development teams, and the integration of AI agents in cloud development environments.
Agentic AI is seemingly set up for favourable outcomes. Or is it? Agentic AI is believed to shake-up enterprise IT, offering a productivity boost similar to the iPhone's impact.
This isn't about replacing developers but amplifying their output tenfold. It aims to allow the implementation of rapidly created solutions and iteration that has been unimaginable in the past. This shift requires valuing "soft skills" like communication and collaboration over pure coding proficiency, as developers guide AI "pair programmers."
The synergy of AI agents, human intellect, and Cloud Development Environments (CDEs) is key. CDEs provide secure, governed, and scalable platforms for this collaboration, allowing developers to focus on business logic and innovation while AI handles the coding groundwork. This requires a move from rigid "gates" in development processes to flexible "guardrails" within CDEs. Such a move fosters innovation with built-in control and security.
Flexibility and choice are vital in this constantly advancing AI space. CDEs enable organisations to select the best AI agents for specific tasks, avoiding vendor lock-in by expressing the development environment as code. This leads to practical applications like faster prototyping, enhanced code development, and automated testing, significantly boosting code output. Furthermore, agentic AI democratises development, empowering non-engineers to build solutions.
Preparing for this future requires proactive experimentation through AI labs, engaging early adopters, and viewing AI as an augmentation of human skills. Watch the podcast for more insights on CDEs and the impact of AI agents on enterprise cloud development.
TakeawaysAgentic AI is a transformative technology for software development.
The role of developers is shifting from hard skills to soft skills.
AI agents can significantly increase productivity in coding tasks.
Organizations need to rethink their development strategies to integrate AI.
Cloud development environments are essential for safely using AI agents.
Choosing the right AI agent is crucial for effective development.
Security and governance are critical when integrating AI into development.
AI can empower non-developers to create applications.
Guardrails are more effective than gates in managing AI development.
Organisations should experiment with AI to find the best fit for their needs.
Chapters00:00 Introduction to Agentic AI and Developer Roles
03:20 Transformative Impact of AI on Development
06:50 Cultural Shifts in Development Teams
10:30 Integrating AI Agents in Cloud Development Environments
12:49 Choosing the Right AI Agents
15:21 Security and Governance in AI...
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Takeaways
#Customersuccess is about helping customers get value from products.The perception of customer success is shifting from a cost centre to a revenue generator.#AI can enhance customer success by providing predictive insights and automating processes.Customer success teams are uniquely positioned to identify upsell and cross-sell opportunities.Collaboration between customer success and sales teams is essential for maximising revenue.The integration of AI tools can streamline customer success operations.Summary
Ever wonder how to transform existing customers into your company’s most powerful growth engine? According to Gainsight’s Chief Revenue Officer, Marilee Bear, it starts with one deceptively simple principle: “helping customers get value from your product.”
This #TechTransformed episode features Christina Stathopoulos, Founder of Dare to Data, in conversation with Marilee about the dynamic role of customer success – a powerful avenue for building deeper customer bonds, boosting retention rates, and ultimately achieving significant revenue gains.
Tune in to learn how to unlock the potential of customer success as a catalyst for cross-selling and upselling opportunities. Explore how to equip your customer success teams with commercial acumen and harness their potential as a secret weapon for business growth.
Whether you're a #CRO looking to optimise revenue or a business leader navigating the AI revolution, this episode offers invaluable insights into the future of customer success.
For the latest tech insights visit: EM360Tech.com
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Takeaways
#AgenticAI systems can string tasks together for efficiency.Real-world applications include supply chain optimisation and knowledge worker augmentation.#Dataquality is crucial for effective AI implementation.Education and understanding of AI's potential are essential for organisations.Governance is key to ethical AI deployment.Leadership is critical in adopting AI technologies.AI will create new job opportunities, not just displace existing ones.Summary
Jeff DeVerter, Field Chief Technology Officer at Pythian, describes agentic AI as “little workers that are going to go off and all do a job. You're now a manager of these AIs that are going to go off and do some work and come back and give you that work product.”
In this episode of the #TechTransformed podcast, Christina Stathopoulos, Founder at Dare to Data, and Jeff DeVerter explore this concept, revealing how agentic systems are re-shaping real-world business scenarios.
Imagine these agentic AIs as powerful “personal assistants” when empowering leaders to manage data, streamline workflows and drive commercial acumen.
The discussion goes beyond the possibilities addressing how to prepare your data infrastructure, navigate ethical considerations, and understand AI’s impact on employees, delivering crucial takeaways for CIOs.
For the latest tech insights visit: EM360Tech.com
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From the integrities of the human workforce embracing enhancing soft skills over hard skills in the enterprise tech space to the adoption of artificial intelligence (AI) agents in customer service, this conversation covers it all.
In this episode of the Tech Transformed podcast, Shubhangi Dua speaks with Nikhil Nandagopal, co-founder and CPO of Appsmith, about the metamorphological impact of AI agents in the workplace. He particularly emphasises the need for organisations to hone in on the advancing capabilities of agentic AI while still maintaining a focus on human collaboration and security.
Takeaways
AI agents are autonomous entities designed to achieve specific goals.The centralisation of data through AI agents simplifies workflows.Conversational interfaces are becoming the norm for accessing information.Humans remain integral to AI workflows, acting as moderators.Job roles will evolve, requiring new skills and adaptability.Critical thinking is essential when interacting with AI outputs.Cybersecurity is a major concern with centralised AI systems.Self-hosting AI solutions can mitigate cybersecurity risks.The future of work will reward soft skills over hard skillsChapters
00:00 Introduction to AI Agents and Their Impact
03:34 The Shift Towards Conversational Interfaces
05:07 Assisted Workflows and Human-AI Collaboration
10:05 Job Market Evolution in the Age of AI
13:23 Critical Thinking in the Age of AI
15:29 Cybersecurity Concerns with AI
20:31 Preparing for Cyber Threats in AI Systems
22:51 The Future of AI Agents in the Workplace
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In this episode of the Tech Transformed Podcast, Jon Arnold, Principal of J Arnold Associates speaks with Nikola Mrksic, CEO of PolyAI, discussing all things AI, specifically in contact centres. From the benefits of automation to the emergence of the most trending subject of the year – Agentic AI.
Mrksic particularly spotlights some underutilised capabilities of AI such as how it can manage up to 90% of repetitive duties, allowing human agents to concentrate on other complex tasks. The conversation also explores the transition from basic service to a broader, more holistic customer experience, necessitating the need for rapid adaptation and experimentation.
AI in contact centers isn't just about cutting costs. This conversation shows how it can truly make a difference – giving agents the tools to shine, providing customers with better, more quality experiences, and even letting AI take care of tasks behind the scenes securely, so humans can focus on what truly matters.
Takeaways
AI is a dominant force shaping technology today.Contact centers have a high volume of repetitive tasks suitable for AI.AI can automate up to 90% of tasks in contact centers.The role of AI is not just cost-cutting but improving service quality.Agentic AI can perform tasks on behalf of users asynchronously.Customer experience is now a key focus beyond just service.Companies must adapt quickly to avoid falling behind competitors.Failing fast and experimenting is crucial for success with AI.AI can provide insights that traditional methods miss.Investing in AI should be about solving problems, not just keeping up with trends.Chapters
00:00 Introduction to AI in Contact Centers
02:01 Benefits of AI in Contact Centers
07:37 Transforming Customer Experience with AI
15:42 Understanding Agentic AI
21:27 The Shift from Customer Service to Customer Experience
30:25 Advice for Business and CX Leaders
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The world is changing faster than ever. Businesses are drowning in data, yet struggling to extract the insights they need to stay ahead. Artificial intelligence (AI) holds the key, but traditional AI models are too slow, too static, and too disconnected from the real world. This is where real-time AI comes in.
Real-time AI empowers businesses to make decisions in milliseconds, reacting to changing conditions and seizing fleeting opportunities. It's about more than just analysing historical data; it's about understanding the present and predicting the future, all in the blink of an eye.
Imagine a world where customer service agents have access to the most up-to-the-minute information, resolving issues before they escalate. Envision supply chains that dynamically adjust to disruptions, ensuring products are always available. Envision marketing campaigns that personalise experiences in real time, maximising engagement and driving conversions.
But real-time AI isn't just about speed; it's also about accuracy. The time to embrace real-time AI is now. Businesses that fail to adapt risk falling behind in an increasingly competitive world. By harnessing the power of real-time data and intelligent agents, enterprises can tap into new levels of performance, innovation, and growth.
In this episode, Shubhangi Dua, an editor and tech journalist at EM360Tech, speaks to Madhukar Kumar, the Chief Marketing Officer at SingleStore, about the transformative potential of real-time AI for enterprises.
Takeaways
Real-time AI is essential for modern enterprises.The evolution from generative AI to real-time AI is significant.Data accuracy and freshness are critical for AI success.AI agents will collaborate to enhance business processes.Enterprises must manage data silos to improve efficiency.Smaller companies can leverage AI to create innovative solutions.Data governance is crucial for protecting sensitive information.Real-time AI can significantly improve user experience.AI will enable professionals to focus on higher-value tasks.Harnessing data effectively will be a key differentiator for businesses.Chapters
00:00 Introduction to Real-Time AI and Its Importance
03:03 The Evolution of AI: From Generative to Real-Time
05:54 Real-Time AI in Enterprises: Advantages and Examples
11:01 The Future of AI Agents and Their Collaboration
16:47 Preparing Enterprises for AI: Data Management and Security
20:47 Business Advantages of Real-Time AI and Future Opportunities
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In this conversation, Ryan Worobel shares his extensive experience in the technology sector, discussing the evolution from traditional monitoring to observability. He highlights the cultural and technical challenges organizations face during this transition, emphasizing the importance of collaboration and data management. Ryan also explores the role of AI in enhancing IT operations, advocating for a balance between automation and human expertise. He provides insights on implementing AI in organizations, the risks and opportunities associated with it, and the necessity of understanding company culture for successful adoption.
Key Takeaways
Observability requires a cultural shift towards collaboration.Data management is crucial to avoid overwhelming teams.AI is transforming IT from reactive to proactive approaches.Organizations must start small when implementing AI.Understanding company culture is key to AI adoption.Uptime is essential; downtime is no longer acceptable.AI should supplement human expertise, not replace it.Effective data sorting can reduce noise in decision-making.Innovation is necessary to maintain a competitive edge.Organizations need to establish governance around AI usage.Chapters
00:00 Introduction to Ryan Worobel and His Journey
07:37 Proactive vs Reactive Approaches in IT
13:31 Implementing AI in Organizations
19:31 Conclusion and How to Connect with Ryan
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In this conversation, Sam Page explores the evolving landscape of digital experiences, emphasizing the shift from the information age to the experience age, driven by advancements in AI.
Learn about importance of creating meaningful digital interactions, the challenges posed by biases in AI, and the need for transparency and education in navigating these technologies. Sam introduces a framework for brands to understand, connect, and serve their audiences effectively, highlighting the potential of AI to enhance consumer experiences while addressing concerns about job displacement and data biases.
Key Takeaways
The digital experience is rapidly changing with AI at the forefront.Brands must prioritize meaningful digital experiences to connect with consumers.The shift from the information age to the experience age is significant.AI can create unique experiences tailored to individual needs.Concerns about AI include job displacement and biases in data.Transparency and trust are crucial in AI adoption.Education about AI should start from a young age.Brands can leverage AI to enhance customer connections.Spotify's DJ feature exemplifies effective AI use in consumer engagement.Understanding, connecting, and serving are key components for brands in the AI era.Chapters
00:00 The Evolution of Digital Experience
04:01 Transitioning from Information Age to Experience Age
08:03 Addressing AI Concerns and Biases
14:11 Navigating AI: Understand, Connect, and Serve
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In this conversation, Phillip Mortimer discusses the transformative impact of AI on private markets, emphasizing the unique challenges posed by non-standardized data and the importance of balancing quantitative and qualitative insights in investment decisions. He highlights the significance of data privacy in AI applications and the evolving role of generative AI in automating workflows. Mortimer also addresses concerns about the future of AI, arguing against the notion of reaching an inflection point in returns due to existing limitations.
Key Takeaways
AI is essential for navigating the complexities of private markets.Data scarcity and non-standardization make AI a necessity in finance.Human intuition remains crucial in investment decision-making.AI can enhance productivity but should not replace human judgment.Generative AI poses new data privacy challenges that must be addressed.Last mile SaaS can still thrive despite the rise of generalized AI.The future of AI is promising, with ongoing advancements in technology.Type 2 thinking in AI is a key area for development.Investors must consider the return on intelligence, not just ROI.AI's role in finance is to augment human capabilities, not replace them.Chapters
00:00 Introduction to AI in Private Markets
02:56 The Role of AI in Data Analysis
06:00 Balancing Quantitative and Qualitative Insights
08:50 Data Privacy Concerns in AI
11:54 Generative AI and Last Mile SaaS
14:59 Future of AI and Investment Returns
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In this conversation, Michel Spruijt discusses the integration of AI and robotics in various industries, emphasizing the importance of balancing automation with human oversight. He highlights the challenges of designing multifunctional AI systems and the critical role of data interpretation in ensuring ethical use. Michel also shares insights on how organizations can adapt to AI, the significance of curiosity in career development, and the evolving job landscape due to technological advancements.
Key Takeaways
AI and robotics are transforming industries, including cleaning.The balance between automation and human oversight is crucial.Data interpretation is more important than just data collection.Organizations should start small with AI investments.Curiosity is key to identifying unique opportunities in careers.AI will create new jobs while automating others.Human oversight is essential for ethical AI use.Staying curious can lead to career growth and innovation.AI should complement human work, not replace it.Understanding AI's capabilities can enhance productivity.Chapters
00:00 Introduction to AI and Robotics in Industry
03:00 The Balance of Automation and Human Oversight
05:56 Challenges in Designing Multifunctional AI Systems
08:48 Data Interpretation and Ethical Considerations
12:07 Adapting Organizations to AI
16:58 Identifying Unique Opportunities in AI Roles
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The rise of artificial intelligence (AI) is transforming industries, and customer success is no exception. Current trends show a rapid increase in AI adoption. This is driven by the potential to personalise interactions, automate routine tasks, and gain valuable insights from customer data among other solutions.
However, the transition requires careful consideration of how AI can blend with existing customer success practices. The goal is to ultimately develop a combination of AI capabilities and human empathy, leading to more satisfying and effective customer experiences.
This is where natural language processing (NLP) comes in. The power of NLP can be leveraged to understand customer queries and sentiment analysis to determine their emotional state.
In this episode, Kevin Petrie, VP of Research at BARC, speaks to Kate Neal, Senior Director of Customer Success at Gainsight, about the evolving role of AI in customer success.
Takeaways
AI adoption in customer success is accelerating despite some hesitations.Gainsight provides a comprehensive customer operating system, “powered by AI”.Natural language processing can significantly enhance customer sentiment analysis.Human oversight is crucial in AI applications to ensure accuracy.Data quality is essential for effective AI implementation.AI can help reduce the administrative burden on customer success teams.Collaboration between data and AI teams is necessary for success.Understanding AI's capabilities is key for customer success leaders.AI is not a replacement for human jobs but a tool to enhance them.Chapters
00:00 Introduction to AI in Customer Success
03:44 Gainsight's Role in Customer Success
07:11 AI Adoption Trends in Customer Service
10:51 Use Cases of AI in Customer Success
15:12 Natural Language Processing and Customer Sentiment
19:48 Human Oversight in AI Applications
22:06 Collaboration Between Data and AI Teams
23:59 Getting Started with AI in Customer Service
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James Smith discusses his extensive background in business intelligence and analytics, emphasizing the critical importance of adopting generative AI in organizations. He highlights the risks of delaying adoption, the transformational potential of AI, and the need for alignment between AI and business strategies. James also addresses the importance of measuring the impact of AI, ensuring ethical use, and leveraging AI to anticipate future trends. He concludes by sharing insights on how businesses can effectively implement generative AI to gain a competitive edge.
Key takeaways
Generative AI adoption is crucial for maintaining competitive advantage.Organizations that delay AI adoption risk losing market share.AI can transform the role of data teams in organizations.Effective communication is essential during AI implementation.Aligning AI strategy with business goals is critical for success.Measuring ROI is more important than just tracking user adoption.Keeping humans in the decision-making loop is vital for ethical AI use.Generative AI can empower all employees, not just a few.Organizations should test AI solutions against complex use cases.Chapters
00:00 Introduction to James Smith and His Background
03:12 The Importance of Generative AI Adoption
06:05 Transformational Potential of Generative AI in Organizations
08:54 Measuring the Impact of Generative AI
11:54 Aligning AI Strategy with Business Goals
15:05 Addressing Bias and Ensuring Ethical AI Use
18:09 Leveraging Generative AI for Future Trends
23:51 Conclusion and How to Connect with James Smith
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Azfar Aslam, VP & Chief Technology Officer, Europe at Nokia discusses the evolving landscape of telecommunications, focusing on the integration of AI and quantum computing. He highlights the challenges of implementing AI in network management, the importance of quantum safe cryptography, and the need for reliability in technology. The discussion also touches on the competitive nature of the industry and the ethical considerations of AI, particularly in ensuring fairness and avoiding biases in decision-making.
Key Takeaways
AI is transforming telecommunications but comes with challenges.Focus on solving big problems rather than getting lost in technology.AI-powered maintenance can prevent outages and improve reliability.Quantum computing has the potential to revolutionize network security.Organizations must prepare for the transition to quantum-safe cryptography.Reliability and trust are critical in adopting new technologies.Competition in telecommunications is fierce, requiring constant innovation.AI systems must be designed to avoid biases and ensure fairness.Traceability in AI decision-making is essential for accountability.The balance between technology and economics will drive future innovations.Chapters
00:00 Introduction to AI in Telecommunications
02:48 Challenges of AI Implementation
06:11 The Role of Quantum Computing
12:01 Quantum Safe Cryptography
15:10 The Future of Quantum in Telecommunications
17:58 Competition and Reliability in Tech
20:54 Ensuring Fairness in AI Systems
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Hear Matt Yates explore the transformative role of AI in contact centers, discussing technologies like natural language processing and sentiment analysis. They delve into the balance between AI efficiency and the irreplaceable human touch in customer service, highlighting the importance of transparency, training, and continuous improvement in AI integration.
Key Takeaways
AI is revolutionizing contact centers and customer interactions.Natural language processing is key to understanding customer sentiment.Human agents are essential for nuanced customer interactions.AI models are not 100% accurate and can introduce bias.Transparency in AI decision-making is crucial for customer trust.Organizations should balance AI efficiency with human emotional intelligence.Predictive analytics can enhance customer loyalty and service.Continuous training is necessary for both agents and AI systems.Implementing AI should be done gradually to avoid disruption.Data-driven decision-making is vital for successful AI integration.Chapters
00:00 Introduction to AI in Contact Centers
06:02 The Role of Human Agents in AI-Driven Environments
11:49 Ensuring Transparency and Accountability in AI
17:53 Using Predictive Analytics for Customer Loyalty
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Hear Wilson Chen discuss the complexities of AI in data analysis, particularly focusing on the challenges of bias, misinformation, and the importance of human expertise in interpreting AI-driven insights.
Wilson shares insights from his experience as the founder of Permutable AI , a startup that builds real-time LLM engines, and emphasizes the need for a balanced view in understanding geopolitical trends and market intelligence. The discussion also highlights the critical checks necessary to ensure the accuracy and reliability of AI-generated information.
Key Takeaways
AI systems can amplify existing biases in data.A balanced view of information is crucial for accuracy.Human expertise is essential in interpreting AI outputs.Organizations must critically assess AI-driven insights.Real-time data analysis can enhance decision-making.Misinformation can spread if AI is not properly regulated.Ethical considerations are vital in AI usage.The integrity of sources impacts AI reliability.AI can simplify complex geopolitical dynamics.Permutable.ai aims to provide actionable insights for businesses.Chapters
00:00 Introduction to AI and Data Analysis
05:01 Addressing Bias in AI Systems
09:55 The Role of Human Expertise in AI
14:53 Trusting AI-Driven Market Intelligence
20:01 Conclusion and Future Insights
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AI is catalysing the evolution of low-code platforms and reshaping the landscape of low-code development tools. These new technologies can provide a strategic advantage in streamlining internal operations. By leveraging AI effectively organisations are able to deliver truly personalised, adaptive, and intuitive interactions.
However, organizations face challenges adopting these new technologies and risks like AI hallucinations need to be mitigated to ensure reliable outcomes.
In this episode, Paulina Rios-Maya, Head of Industry Relations at EM360Tech, speaks with Nikhil Nandagopal, Co-founder and CPO of Appsmith, about the transformative impact of AI on low-code platforms and application development.
Key takeaways
Low-code platforms are revolutionizing application development.AI tools can generate code but require careful review.Routine tasks can be automated, but decision-making still needs human input.AI adoption comes with challenges like hallucinations and misinformation.Organizations must adapt their culture and processes for AI success.Developers need skills in data modeling and security for AI applications.AI can simplify user interfaces and enhance user experience.Interconnected applications will rely on AI to bridge data gaps.Most AI projects fail due to underestimating necessary changes.Enterprises face more challenges in AI adoption compared to SMBs.Chapters
00:00 - Introduction to AI and Low-Code Platforms
02:59 - The Role of AI in Automating Tasks
05:51 - Challenges and Risks of AI Adoption
09:08 - Essential Skills for Developers in AI
12:01 - Future of Interconnected Applications
14:50 - Realities vs. Hype of AI in Enterprises
- Visa fler
