Generative AI for European Business Leaders

Explore how generative ai works and see real world examples, as the technology moves from analysis to creation, generating music, art, and tags.

Discover how generative AI shifts from analyzing data to creating new content, using massive data to write, paint, and compose with real-world business applications.

Explore how generative ai learns like the human brain using neural networks, data collection, training, and generation, with gan, transformers, and llms powering ChatGPT.

Witness how generative AI transforms real-world outcomes across healthcare, education, and creative fields, from drug discovery and medical image analysis to personalized lesson plans and innovative art.

Treat AI as a creative director, not a magic button, and boost results by providing clear context, constraints, length, and tone. Input quality determines output.

Explore the ethics of creation in ai, addressing bias, hallucinations, misuse, and data privacy while promoting responsible development, transparency, and ethical design from the ground up.

See AI as a strategic partner shaping business models and creating new value, with leaders understanding AI's impact on decisions to accelerate business success.

Position artificial intelligence as a strategic partner already shaping boardroom decisions by crunching data, revealing trends, and delivering insights. Learn how to weave artificial intelligence into your strategy to win.

From dream to data, this lecture traces AI's evolution from philosophical questions in the 1950s to data-driven business strategy today, highlighting milestones like expert systems, machine learning, and deep learning.

AI turns business into a predictive strategy, transforming models and revenue. Netflix, Amazon, Tesla, and Coca-Cola showcase AI as a strategic engine powering value and services such as Salesforce Einstein.

Tap into generative ai to create content, design products, write software, and compose music, and drive sustainability, instant real-time translation, and hyper-personalized 24/7 support.

Explore the key laws shaping AI, with a focus on the GDPR, and learn your rights when AI impacts your data, and how these laws ensure AI is used responsibly.

Explore how the UK applies a toolkit of existing laws to AI, with a deep dive into the GDPR, its principles and rights, and a quick look at Europe’s approach.

Discover the UK legal toolkit shaping AI, including the Equality Act to prevent discrimination and the Health and Safety Act, with a focus on GDPR's daily impact on personal data.

Highlight the GDPR principles for UK personal data use: lawfulness, fairness and transparency; purpose limitation; data minimization; integrity and confidentiality, plus DPIA risk assessment for high risk AI.

Understand your eight fundamental rights under the UK GDPR, including access, correction, erasure, and the powerful right to opt out when AI makes significant decisions without human involvement.

Assess the EU AI act's risk-based rules and their impact on UK businesses operating in Europe, highlighting evolving regulation for generative AI across borders.

Explore the EU AI Act, the first major rulebook for AI, and its risk-based pyramid. Learn how providers and deployers apply a practical compliance checklist in real-world use.

Explain the EU's four-level risk pyramid for AI, from unacceptable and high risk to limited and minimal risk, with safeguards like transparency and human oversight.

Embed EU compliance into operations with regular audits, unbiased data, and transparent AI; protect privacy and keep a human in the loop for critical decisions to avoid fines.

Apply AI governance across healthcare, finance, and marketing, emphasizing high-risk safeguards. Incorporate data protection impact assessments, explicit consent, and transparent data use with human oversight.

Explore how the European Union's first major AI regulation balances innovation with safety by managing risk, promoting transparency, and defining roles for providers and users, with global reach.

Trace AI's rise from decades of steady, rule-free development to a turning point after the 2022 ChatGPT moment, fueling the push for guardrails and regulation.

Define artificial intelligence as systems that think, learn, and act like humans; explain that today’s AI is narrow, excels at one task, and the dream of general AI remains unrealized.

Assess the double-edged nature of ai, balancing life-saving advantages like early tumor detection and real-time fraud alerts with risks from biased data, black-box decisions, and accountability gaps.

The European Union's AI act establishes a landmark rulebook to address privacy, bias, manipulation, and accountability, setting a global precedent for safe, trustworthy AI.

The eu ai act sets guardrails to ban dangerous ai uses and ensure transparency, while fostering innovation for small businesses, with the Brussels effect making it a global standard.

Regulate AI with a four-tier pyramid of risk under the EU AI Act, from unacceptable and high risk to limited and minimal risk, applying stricter rules for higher harm.

Identify the four key players: providers, deployers, importers, and distributors, and their duties for high-risk AI, including risk management, data quality, human oversight, monitoring, and AI literacy.

Launches a centralized EU AI office to oversee high-risk models and imposes penalties up to €35 million or 7% of global revenue, with phased enforcement through 2027.

The EU AI act rewrites governance of powerful AI models with extraterritorial reach, aiming to set a global benchmark like GDPR, with obligations starting August 2, 2025.

Define the AI Act's general purpose AI model (GPI), explain models versus systems, and note how foundational models like large language models and image generators enable wide task ranges.

Regulators use the proxy of total training compute, capped at ten to the 22nd flops, to gauge model generality; the rule is rebuttable and hinges on capability, not size.

The act places all compliance duties on the GPI model provider, including developers, buyers, and those uploading to public repositories, with downstream modifiers inheriting duties for changes after significant compute.

Prepare to meet EU guidelines by mid-2025, apply by August 2, 2025, and follow a six-step plan: understand basics, train staff, assess risks, develop governance, update contracts, check intellectual property.

Explore how generative ai transforms content creation and personalized experiences while addressing risks such as deepfakes, biases, and privacy, guiding transparency and intellectual property considerations.

Embrace generative ai as a creative partner that boosts innovation and speeds up brainstorming and prototyping. Balance its opportunities with risks like deep fakes and misinformation that threaten reputation.

Navigate the ethical minefield of generative ai by addressing hidden biases, privacy, and the risk of malicious use, and choose a responsible path that prevents deception, discrimination, and fraud.

Generative AI is rewriting the rules of competition across industries, making adaptation essential as early adopters gain a competitive edge through AI-driven art, personalized shopping, and drug discovery.

Clarify ownership of AI-assisted creations, from logos to inventions, amid a legal gray area and evolving patent rules. Examine fair use and training data implications for AI's future.

Balance innovation with integrity by adopting transparent AI usage, accountable governance, and strict data privacy. Use established ethical AI frameworks to guide how your organization deploys generative AI.

Use AI for data visualization and automated data cleaning to speed up processes and increase accuracy; predict trends, guide strategies, enable collaborative decisions, with data security and responsible AI usage.

Turn numbers into visuals with artificial intelligence to reveal clear insights from a data sea, shifting from static to dynamic visuals and prioritizing security for strategic decisions.

Generative AI transforms visuals from static charts to interactive, dynamic dashboards. Automation cleans data, detects errors, and enables forecasting, turning past insights into forward-looking business decisions.

Learn how ai-powered visuals empower real-time data exploration, what-if scenario planning, and cross-functional collaboration from a single source of truth, delivering customized insights for marketing and finance.

Explore an accessible ecosystem of ai-powered analytics tools—from Tableau and Power BI to Qlik Sense and Sisense—that automate insights and deliver interactive dashboards and predictive analytics.

Generative AI visualizations transform static reports into interactive tools, delivering predictive insights and smarter decisions, while embedding privacy by design, anonymization, and audits to enable trust.

Shape the future with AI by reshaping industries and aligning strategies with ethics, as machine learning powers AI systems and high quality data fuels AI leadership through transparency and collaboration.

Lead in the age of ai by embracing a present-day mandate, mastering core tools, and building a clear strategic vision, ethical responsibility, and a culture designed to innovate.

Build your toolkit by speaking the language of AI and mastering data-driven machine learning, including supervised and unsupervised methods, to automate decisions and unlock personalized experiences through high-quality data.

Apply a practical compass for generative AI leadership by demanding transparency, mitigating bias, and defining accountability to build trust with customers and employees. Prioritize human oversight for high-stakes decisions.

Prepare your people for the AI journey by embracing change and cross-functional experimentation. Lead by example, invest in continuous learning, and view failure as data toward breakthroughs.

Define and communicate a clear vision for how ai drives your business forward, align teams, and turn experiments into a unified strategy with concrete steps and pilots.

Develop a growing ai strategy with ongoing attention and change by asking the right business questions, building a skilled team, acting responsibly, and measuring success to improve.

Develop an actionable ai strategy by building a durable blueprint, avoiding hype, and laying a strong foundation across five critical areas to ensure ai initiatives thrive like a garden.

Ask the right questions to build a sustainable generative AI strategy that aligns with business goals, emphasizes data quality, team learning, ethics, and a stepwise checklist.

Invest in your people to harness generative AI for European business leaders; foster a learning culture with hands-on projects, mentorship, and mandatory ethical training to empower teams.

Measure the ROI by inspecting your project’s structure, costs, and performance. Track investments in software, training, and infrastructure against returns like revenue, efficiency, loyalty, and user adoption, using KPIs.

Develop a sustainable, responsible AI strategy that evolves with the landscape through ethical oversight, bias reduction, explainable decisions, accountability, data protection, and ongoing evaluation.

Explore the risks of AI in business, including job displacement, bias, privacy and security, and learn how transparency and high-quality data enable safe, responsible AI.

Explore how AI promises automation and creativity while introducing risks like bias, misinformation, privacy concerns, and job displacement; learn to manage transparency, security, and trust in work and society.

Explore AI hallucinations, where systems make up information with confidence. They fabricate facts, cite nonexistent sources, and invent events due to data gaps, a human-like algorithm, and misinterpreting prompts.

Protect people by keeping a human in the loop, ensure transparency and data privacy, and educate teams on ai tools; use clean, representative data and monitor for bias.