What do you do if you're an executive wanting to keep up with the latest AI technologies and trends?

The best AI-related goals are granular and level-specific, linking the AI outputs to real use cases that combine with one another and lead you to achieve your larger business goals. Here are some points for defining your AI goals: 1. Be Specific: Clearly define what AI outcomes you want to achieve. 2. Measure Progress: Set measurable KPIs to track success. 3. Align with Business Goals: Ensure AI goals contribute to overall business objectives. 4. Time-Bound: Set deadlines for achieving milestones. 5. Relevance: Prioritize goals that directly impact business value.

To stay current with AI technologies and trends as an executive, assess your AI knowledge, understand business needs, stay informed, network with experts, set specific goals, create an action plan, and embrace continuous learning. By doing so, you can lead your organization in leveraging AI to achieve its goals and maintain a competitive edge.

Executives don't have time to squander on the hype and hyperbole in the AI marketplace of technology, services, and ideas. Even before experimentation begins, form a cross-functional AI board to define a portfolio of potential projects that would improve operations, benefit the customer and/or employee experience, or grow the business in ways that would have been time and cost-prohibitive in the past. Connect with industry peers and automation leaders as well as internal teams. Choose a few projects that are 1-2 months in duration and experiment. As you experiment, consider the foundation tech required for Responsible AI to maximize existing IT investments. Modernize where needed, such as LLM orchestration and governance across models.

Determine the specific areas of AI that are most relevant to your business objectives and interests. This will guide your learning journey and help you focus on acquiring knowledge that aligns with your goals.

In my journey, I realized early on that AI could revolutionize the way we approach in-house corporate legal practice, especially with mundane tasks like contract review and compliance checks. For instance, I set a goal to implement an AI system that could sift through thousands of contracts, identifying key clauses and potential issues faster than a caffeinated intern on their first day. To make this happen, I had to assess our firm's readiness, which meant upgrading our digital infrastructure and providing training sessions that felt more like fun AI bootcamps rather than dreary lectures. The result? Our team now navigates legal documents with the ease of a hot knife through butter, allowing us to focus on more strategic initiatives.

To learn the basics of AI as an executive, enroll in online courses, read AI-focused publications, watch tutorials, attend workshops, follow influencers, join communities, and read AI books. Dedicate time to continuous learning to stay current with AI developments.

From quirky AI podcasts that I'd listen to while jogging, transforming each step into a byte of knowledge, to engaging in spirited debates on AI ethics in online forums that felt more like intellectual feasts than discussions. Alongside, I curated a personal library of AI essentials, ranging from beginner's guides to dense scholarly articles, which turned my office into a mini-university. This eclectic approach not only demystified AI for me but also turned learning into an adventure, where each discovery was a step towards responsibly harnessing AI's potential in making legal practices more efficient and humane.

Familiarize yourself with the fundamental concepts of AI, including machine learning, neural networks, natural language processing, and computer vision. There are various online courses, workshops, and resources available to help you gain a foundational understanding of AI.

Understanding Core Concepts: Learning the basics of AI equips executives with a fundamental understanding of core concepts, principles, and techniques in artificial intelligence. This knowledge provides a solid foundation for comprehending advanced AI technologies and trends, enabling executives to make informed decisions and strategic choices. Facilitating Communication: Executives often collaborate with technical teams, data scientists, and AI experts to drive AI initiatives within their organization. Learning the basics of AI allows executives to effectively communicate with these stakeholders, understand technical discussions, and ask relevant questions, facilitating collaboration and alignment across teams.

Ich bin der festen überzeugung, dass man KI und ihre Tools effektiv im Business umsetzen kann, wenn man das Grundprinzip dahinter auch versteht. Die Grundlagen sind elementar um Use Cases im Arbeitsalltag auch "sehen" zu k?nnen. Ein Beispiel aus meinem aktuellen Data Science Studium: Wer nicht wei?, wie ein LSTM funktioniert nimmt beim Prozess Mining einer Produktionshalle vermutlich andere Modelle, die keine Sequenziellen Daten verarbeiten k?nnen. Wie zum Beispiel den XGBoost. Dieser eignet sich jedoch absolut nicht. Warum? Weil er kein Algorithmus ist, der Muster in Sequenzen erkennen kann. LSTM hingegen kann das schon. Au?erdem kann dann der Berater einem nicht einfach alles auf die Nase binden, wenn man auf Stand ist.

To explore the AI landscape as an executive, attend conferences, consult experts, review research, analyze use cases, assess vendors, follow thought leaders, and join AI organizations. These strategies will help you stay informed about the latest AI technologies and trends and their potential applications in your industry.

Understanding Emerging Technologies: Exploring the AI landscape allows executives to familiarize themselves with emerging technologies, methodologies, and trends shaping the field of artificial intelligence. This includes advancements in machine learning, deep learning, natural language processing, computer vision, robotics, and other AI subfields, as well as emerging applications, use cases, and industry trends. Assessing Market Opportunities: By exploring the AI landscape, executives can identify market opportunities and potential areas for investment, innovation, and growth within their industry or sector.

Whether you’re an executive or a junior professional, the most effective way to get up to speed is to try out apps, use gen AI tools, especially ChatGPT, Gemini or Copilot on a daily basis wherever you can, so it becomes second nature, and read articles and news to understand how it all fits together.

It’s incredibly difficult to integrate cutting edge research into how AI will impact your organisation with tremendous risk. But, in understanding how to navigate that risk, through independent creative research labs that derisk orgs and all them to avoid the onboarding new talent that may not need to sit in their business. In this sort of collaborative approach the transfer of skill, knowledge and data is pivotal in staying competitive and maintaining the best possible outcome for the company

Investigating the broad and dynamic AI landscape is akin to conducting thorough market research. It involves identifying not only the technologies that are directly applicable to your industry but also learning from the broader successes and failures in the AI domain. This perspective prioritizes strategic exploration over casual observation, highlighting the value of informed selection and application of AI technologies.

Initiate pilot projects within your organization to test and learn from AI tools in a controlled, risk-managed environment. These experiments can provide hands-on experience and tangible insights into the potential of AI.

Stay informed about the latest advancements, trends, and innovations in AI by regularly reading industry publications, attending conferences, and engaging with AI experts and communities. This will enable you to identify emerging technologies and opportunities that could benefit your organization.

Direct engagement with AI tools and platforms is a proactive step towards demystifying AI and uncovering its practical value. This hands-on approach encourages experimentation and innovation, moving beyond theoretical understanding to actual application. It’s about embracing a culture where trial, error, and eventual success with AI tools are viewed as critical learning opportunities.

The easiest way to experiment with AI tools is to start with one of the big platforms such as Microsoft Cognitive Services or Google Cloud AI. There are several out-of-the-box models you can use and experiment with building your applications to start learning AI.

A survey in Nov 2023 found that 76% of SaaS companies have started using AI, and a further 22% are thinking about it. If your business is not experimenting with AI now, you are behind the curve. With that said, Tech Jury found that only 35% of SaaS companies are developing AI directly. Most are using 3rd party AI tools. Customer services is a popular starting point. So, it is not necessary to understand the intricacies of AI, or to hire AI professionals. Your initial focus should be on whether AI-enhanced tools can improve your business, whether that is lower cost, faster responses, high quality, happier customers, etc. Once a small pilot shows potential, you can then revisit whether you need AI customised to your business.

Embracing collaboration, I reached out to consultants with a knack for demystifying complex algorithms, researchers whose insights illuminated our path, and developers who could weave code into solutions as elegantly as poets do with words. This partnership was not a mere delegation of tasks but a fusion of minds, sparking a culture of curiosity and mutual learning within our team. We held regular 'AI jam sessions,' where ideas flowed freely, and everyone, from interns to seasoned lawyers, was encouraged to share, challenge, and build upon each other's insights. This collaborative spirit accelerated our AI journey and turned our workplace into a vibrant learning hub, echoing the sounds of innovation and teamwork.

Access to Specialized Knowledge: AI experts possess specialized knowledge, expertise, and insights in various aspects of artificial intelligence, including algorithms, methodologies, tools, and applications. Collaborating with AI experts allows executives to tap into this wealth of expertise and gain valuable insights into emerging technologies, trends, and best practices in the field. Strategic Guidance and Advice: AI experts can provide strategic guidance and advice to executives on navigating the complex landscape of AI technologies and trends. By leveraging their expertise.

I believe that for an executive seeking to stay updated on the latest AI technologies and trends, collaborating with AI experts is essential. This means fostering partnerships with leading AI research institutions, consulting firms, and technology providers. By leveraging the expertise of these professionals, executives can gain valuable insights into emerging AI advancements, industry trends, and potential applications relevant to their business objectives. Additionally, participating in AI-focused, conferences, and webinars provides opportunities to network with other leaders and exchange knowledge, ensuring executives remain informed and well-equipped to make strategic decisions regarding AI integration within their organizations.

Partnering with AI experts transcends the simple acquisition of external expertise; it's about integrating these insights to accelerate the organization's AI initiatives. This collaboration is not just a pathway to technological advancement but also a strategy to foster an internal culture of learning and innovation. It emphasizes the collaborative effort required to navigate the complexities of AI technology and implement it successfully.

I think acquainting myself with common AI terminology and tools used in the field, such as algorithms, models, Python, TensorFlow, PyTorch, AWS, Azure, and Google Cloud helps a lot. Understanding these elements will help us communicate more effectively with AI experts and developers. For collaboration I'm using tools designed for remote teams, such as Taskade, which offers features for project management, real-time chat, video conferencing, and AI-powered task automation. My current AI project is Jetson Nano JetRacer. The JetRacer AI is an advanced AI racing robot kit designed with the NVIDIA Jetson Nano Developer Kit. It is intended for deep learning applications, auto line following, and autonomous driving.

Network network network. It's much easier to be part of a group or wave getting updated on the latest trends in AI than it is doing it solo - up to a point. Leverage networks and communities to get pointed in the right direction, but also have the courage to break away and pursue a particular niche or specialization. I think there are too many ML, Analytics, Data Science cheerleaders - less on data engineering, ethics, safety, and domains such as automation, creativity, knowledge management, change management, etc. Like the internet, AI will soon be just another aspect of our lives, unlike some other tech that seem to continue to be self-important for their time. Hype cycles end eventually, just weather it out, and build true knowledge.

As an executive keeping up with AI: 1. Follow industry leaders and thought influencers on social media. 2. Attend AI conferences, webinars, and workshops. 3. Engage in executive education programs focused on AI. 4. Collaborate with AI experts within your organization. 5. Subscribe to AI newsletters and publications for regular updates.

This field is evolving at such lightning-fast speed that staying on top of all the trends is a full-time job. The quickest and simplest way is to set Google alerts for "LLM" "OpenAI" "Claude" "Gemini". If you check these alerts daily, you will probably be in a good spot.

All you need is FOCUS: F: Follow Industry stalwarts around AI O: Observe how the AI industry is evolving C: Collaborate in AI related discussions in forums U: Update your knowledge with the fundamentals S: Subscribe to AI newsletters

Continuous learning is THE most important skill in the AI era. This was one of the conclusions of Davos, WEF 2024. Learning is much more than following trends. Learning in the AI era is learning from others, being curious, asking questions, testing and doing, among others