How Generative AI is Transforming Job Roles in IT

In the previous issue of my newsletter, I addressed the topic of how to become an AI agent developer to help programmers expand their skills (Mastering AI - How to Become an AI Agent Developer with Microsoft Technologies in 2024 ). Today we address a related but much broader topic, namely, how I see the evolution of roles in the IT with the advent of generative AI. I imagined myself writing job posts for some roles that exist today but updated with AI-related skills and some new roles that will come. Please don't take this study of mine too seriously; nevertheless, it is meant to be food for thought for the future.

Artificial Intelligence (AI) is rapidly revolutionizing the IT landscape, automating routine tasks, and creating new employment opportunities in machine learning, data analytics, and AI ethics (to mention a few in IT). This new AI-oriented workforce presents challenges and prospects for IT professionals compelled to adapt and evolve in different roles.

I imagined myself writing job posts for some roles that exist today but updated with AI-related skills and some new roles that will come

The Evolution of the Workforce: Why Adaptability and Learning are Key

To embrace changes in existing roles and adapt to new roles in the evolving AI-driven workforce, people should cultivate a growth mindset and be open to continuous learning. This necessity transcends specific industries and job roles, becoming universal across all professions. The reasons for this shift are multifaceted, rooted in the accelerated pace of technological advancements, changing job requirements, and the dynamic nature of the global economy. Being adaptable in the face of these changes is key to feeling resilient and prepared.

Technological advancement revises task execution methods, which entail both advantages and disadvantages. Any professional must constantly update themselves to stay ahead of the curve in their area. For this reason, possessing a growth mindset has become one of those lifelong learning skills because it helps individuals focus on embracing new technologies while adjusting quickly, even when constantly changing.

Henceforth, global labor markets have become ever more competitive because borders no longer restrict talent. Nowadays, any firm can easily tap into the vast global talent pool for an efficient workforce instead of limiting themselves within their national boundaries by hiring a few employees who are just there for globalization's sake. Employees need to keep improving their skills through both education and gaining experience.

In order to solve today's problems in the current competitive landscape, we need interdisciplinary solutions, which, in turn, necessitate collaboration across different fields and expertise. This sense of belonging and cooperation represents the cornerstone of the process. It stimulates an open attitude to learning from other disciplines and integrates diverse knowledge. This approach is beneficial and indispensable for innovation and effective problem-solving.

The Human-AI Partnership

AI is reshaping the landscape of the modern workforce with current jobs changing and new ones created. This shift in job roles revolves around numerous fundamental aspects.

1. This implies that workers have to gain knowledge in new technologies and be able to fit automation into their daily routines. AI automates repetitive tasks which allows human employees to engage in more complex, strategic and creative work. Consequently, employees will have to learn new technical skills and adapt to employing AI in their daily operations.
2. By offering data-driven insights and predictive analytics , AI boosts decision-making processes thus enabling employees to make more informed and effective choices.
3. The rise of AI is an urgent call for us all to keep on learning and improving professionally. The pace at which Technology advances go very past all of us that skills get outmoded quickly so we have no option but pursue knowledge acquisition all time long if we are to be useful in work places.
4. The significance of the synergy between humans and AI systems is on the rise. It, therefore, demands an interlocking between human reasoning and AI power indicating the never-before-existing workforces’ capacity for teamworkfully.

The transformation effects of AI on job roles identify adaptability, upskilling and proactive approaches as critical thereby underscoring these aspects collectively. Let's delve into a few examples to illustrate my points.

How Some Current Jobs Are Changing

Software Developers

Increased focus on AI integration, prompt engineering, and oversight of AI-generated code.

• Paradigm shift: Developers' roles are evolving from writing every line of code to becoming AI orchestrators and quality controllers.
• Productivity boost: AI-assisted coding can significantly increase developer productivity by 2-3 times for specific tasks.
• Skill polarization: There may be a growing divide between developers who can effectively leverage AI and those who can't, which could impact career trajectories.
• Reduced entry barrier: AI coding assistants might lower the barrier for entry-level programming, potentially disrupting traditional software education.
• Code quality concerns: While AI can generate code quickly, it becomes crucial to ensure its quality, security, and alignment with best practices.

Suggestions

• Continuous learning: Developers should allocate time to stay updated on the latest AI tools and techniques in software development.
• Prompt engineering skills: Invest in learning prompt writing for AI coding assistants to maximize their utility.
• AI-human collaboration workflows: Develop and refine workflows that combine AI assistance with human expertise optimally.
• Ethical considerations: Be aware of potential biases in AI-generated code and ensure adherence to ethical coding practices.
• Specialization in AI oversight: Consider specializing in areas like AI model fine-tuning for coding or AI-generated code review.
• Soft skills development: As AI handles more coding tasks, focus on improving problem-solving, communication, and project management skills.
• Open-source contribution: Participate in open-source AI coding projects to gain hands-on experience and stay at the forefront of this shift.
• Cross-functional collaboration: Work closely with data scientists and AI specialists to better integrate AI into software development processes.
• Performance metrics adaptation: Develop new metrics to measure productivity that account for AI assistance in the development process.
• AI limitations awareness: Understand the current limitations of AI in coding to know when human intervention is necessary.

Data Scientists

Shift towards more complex analysis and model interpretation, with GenAI handling routine data tasks.

• Automation of routine tasks: GenAI is increasingly capable of handling data cleaning, basic feature engineering, and simple model building, freeing up data scientists for more complex work.
• Emphasis on interpretation: As AI models become more sophisticated, data scientists must interpret and explain their results to non-technical stakeholders.
• Increased focus on edge cases: Data scientists tackle more nuanced, complex problems that AI struggles with as GenAI handles common scenarios.
• Ethical considerations: As AI models make more decisions, ensuring fairness, transparency, and ethical use of data becomes a key responsibility.
• Interdisciplinary approach: The role is evolving to require technical skills, domain expertise, and business acumen to derive meaningful insights.

Suggestions

• Advanced statistical knowledge: Deepen understanding of complex statistical concepts to tackle more challenging analytical problems.
• Model interpretability techniques: Master techniques like SHAP (SHapley Additive exPlanations) values, LIME (Local Interpretable Model-agnostic Explanations), and attention mechanisms for neural networks.
• Causal inference skills: Develop expertise in causal inference methods to move beyond correlation and tackle causation questions.
• Ethical AI practices: Stay informed about AI ethics, fairness metrics, and bias mitigation techniques.
• Communication skills: Enhance ability to explain complex models and results to technical and non-technical audiences.
• Domain specialization: Consider specializing in a specific industry or field to provide deeper, context-aware insights.
• AI oversight skills: Develop the ability to evaluate and improve AI-generated analyses and models.
• Synthetic Data Management: Manage the generation and utilization of synthetic data to train machine learning models while ensuring privacy and compliance.
• Cloud and distributed computing: Mastering cloud platforms and distributed computing to manage data storage and computation growth.
• Continuous learning: Stay updated on the latest AI and machine learning advancements through academic papers, conferences, and online courses.
• Experiment design: Strengthen skills in designing robust experiments to test hypotheses and validate AI-driven insights.

IT Support

Enhanced by AI chatbots, allowing human staff to prioritize more complex issues and focus on strategic improvements. This shift in IT Support represents a move towards a more strategic and analytical role. Support staff are becoming orchestrators of AI-powered systems, problem-solving experts for complex issues, and key drivers of service improvement.

• Tiered support structure: AI chatbots are becoming the first line of support, handling common issues and FAQs, allowing human staff to focus on more complex, nuanced problems.
• 24/7 availability: AI-powered support systems enable round-the-clock assistance, improving user satisfaction and reducing the pressure on human staff to be constantly available.
• Data-driven improvements: AI chatbots generate vast interaction data, providing insights for continual service improvement.
• Skill shift: The role moves from repetitive troubleshooting to more strategic, analytical, and improvement-focused tasks.
• User behavior change: As users become more accustomed to AI-first support, their expectations and interaction patterns with IT support are evolving.

Suggestions

• AI management skills: Develop expertise in managing, monitoring, and optimizing AI-powered support systems.
• Advanced troubleshooting: Focus on enhancing skills for complex, non-routine issues that AI cannot handle.
• Data analysis: Improve abilities to analyze AI-generated support data for insights and service improvements.
• User experience design: Learn to design and improve user interfaces and experiences for AI-human hybrid support systems.
• Emotional intelligence: Enhance soft skills to handle escalated issues where users may be frustrated after interacting with AI.
• Continuous learning: Stay updated on emerging technologies and potential IT issues to remain ahead of user needs.
• Knowledge base management: Develop skills in creating and maintaining comprehensive, AI-friendly knowledge bases.
• Cross-functional collaboration: Work closely with development teams to provide insights for product improvements based on support data.
• Change management: Develop skills to help users adapt to new AI-enhanced support systems and self-service options.
• Process optimization: Learn to identify opportunities for automating additional support processes using AI.
• Metrics and KPI evolution: Develop new metrics and KPIs that accurately reflect the performance of AI-human hybrid support systems.

Cybersecurity Specialists

Greater emphasis on AI-related security risks and ethical AI implementation.

• New attack vectors: AI systems introduce novel vulnerabilities and attack surfaces that cybersecurity specialists must understand and protect against.
• AI-powered threats: Malicious actors leverage AI to create more sophisticated attacks, requiring equally advanced defense mechanisms.
• Data privacy concerns: The use of AI in cybersecurity raises new questions about data privacy and regulatory compliance.
• Ethical considerations: Balancing security needs with ethical AI use becomes critical to the cybersecurity specialist's role.
• Rapid evolution: The AI security landscape changes quickly, requiring constant vigilance and adaptation.

Suggestions

• AI security expertise: Develop a deep understanding of AI/ML models, their vulnerabilities, and how they can be exploited or defended.
• Adversarial ML knowledge: Learn about adversarial machine learning techniques and how to defend against them.
• Ethical AI frameworks: Familiarize yourself with ethical AI guidelines and best practices for implementing them in security contexts.
• Advanced threat detection: Enhance skills in using AI for threat detection while protecting these systems from manipulation.
• Privacy-preserving techniques: Learn about federated learning and differential privacy for secure, privacy-preserving AI implementations.
• Regulatory compliance: Stay updated on AI-related regulations and their implications for cybersecurity practices.
• Explainable AI: Develop skills in creating and working with explainable AI models to ensure transparency in security decisions.
• Incident response for AI systems: Develop protocols for responding to security incidents involving AI systems.
• Continuous learning: Stay abreast of the latest developments in AI security through academic papers, conferences, and specialized training.
• Red teaming for AI: Enhance ethical hacking and penetration testing skills specifically for and with AI systems.
• Risk assessment: Develop frameworks for assessing and quantifying AI-specific security risks.

Project Managers

Need to adapt to AI-augmented project planning and resource allocation.

• Enhanced predictive capabilities: AI enables more accurate forecasting of project timelines, costs, and potential risks.
• Dynamic resource allocation: AI algorithms can optimize resource allocation in real-time, adapting to changing project conditions.
• Automated routine tasks: Many administrative and reporting tasks allow PMs to focus on strategic decision-making.
• Data-driven decision-making: AI provides deeper insights from project data, enabling more informed decision-making.
• Increased complexity: While AI simplifies some aspects, it introduces new complexities in implementation and stakeholder management.

Suggestions:

• AI literacy: Develop a strong understanding of AI capabilities and limitations in project management contexts.
• Data analysis skills: Enhance abilities to interpret and act on AI-generated insights and predictions.
• Adaptive planning: Learn to work with more dynamic, AI-driven project plans that can change rapidly based on new data.
• Human-AI collaboration: Develop skills in effectively combining AI recommendations with human judgment and experience.
• Ethical considerations: Understand the ethical implications of AI in project management, including bias in decision-making algorithms.
• Stakeholder management: Improve skills in managing stakeholder expectations and concerns regarding AI-augmented project management.
• Agile methodologies: Strengthen knowledge of agile and hybrid methods that can better accommodate AI-driven changes.
• Technical integration: Learn how to integrate AI tools into existing project management software and workflows.
• Risk management: Develop new approaches to risk management that account for AI-specific risks and opportunities.
• Continuous learning: Stay updated on emerging AI technologies and their potential applications in project management.
• Soft skills enhancement: Focus on developing uniquely human skills like emotional intelligence, creative problem-solving, and conflict resolution.
• Change management: Improve abilities to guide teams and organizations by adopting AI-augmented project management practices.

Careers of Tomorrow: New Job Roles

AI Ethics Officer

The role of the AI Ethics Officer is becoming increasingly critical in today's rapidly evolving technological landscape, as it brings ethical concerns to the forefront of organizational priorities.

As governments worldwide introduce stricter AI regulations, companies recognize the need for dedicated professionals to ensure compliance and navigate the complex ethical terrain of AI implementation.

The growing public awareness of AI's potential negative impacts has increased scrutiny on organizations, compelling them to prioritize ethical AI use to maintain public trust and protect their reputation. The complexity of AI necessitates oversight to ensure fairness, transparency, and accountability. Companies are increasingly aware that unethical AI use poses significant risks, highlighting the importance of the AI Ethics Officer's role in maintaining public trust and protecting the company's reputation.

The AI Ethics Officer operates at the intersection of technology, ethics, and business strategy, collaborating across departments to proactively address potential ethical issues before they become problems. A key aspect of the role involves developing and implementing comprehensive AI ethics policies and guidelines that align with the organization's values and regulatory requirements.

It's essential to continuously evaluate AI systems for bias and ethical adherence as they develop and are used in new situations. The AI Ethics Officer also engages externally by representing the company on AI ethics matters to stakeholders, regulators, and the public. This helps shape the organization's reputation and ethical stance in AI.

Skills required

• Knowledge of ethical philosophy and its application to technology
• Familiarity with AI governance frameworks and relevant regulations
• Excellent communication skills to explain complex concepts to various audiences
• Analytical skills to assess AI systems for potential biases or ethical issues
• Project management abilities to oversee the implementation of ethical AI practices
• Conflict resolution skills to navigate disagreements on ethical issues
• Data analysis skills to work with large datasets and identify patterns of bias
• Knowledge of privacy laws and data protection principles

Suggestions to prepare for the role

• Education: Consider pursuing advanced degrees in AI ethics, philosophy of technology, or related fields.
• Certifications: Look for emerging certifications in AI ethics and governance.
• Interdisciplinary approach: Gain experience or knowledge in tech, ethics, law, and business to develop a well-rounded perspective.
• Stay informed: Regularly read academic papers, attend conferences, and follow thought leaders in AI ethics.
• Gain practical experience: Look for opportunities to work on AI ethics projects, even if not in a dedicated ethics role.

GenAI Prompt Engineer

The role of the GenAI Prompt Engineer has become prominent due to the increasing sophistication and widespread adoption of large language models and other generative AI systems across various industries.

Organizations are realizing that the quality and relevance of AI outputs depend on the prompts used to guide them. This understanding has led to a demand for specialists who can craft and optimize these prompts. Enter the GenAI Prompt Engineers, a unique breed with profound linguistic expertise that is the cornerstone of their role, coupled with technical understanding and creative problem-solving skills that set them apart in the AI landscape.

The emergence of the GenAI Prompt Engineer role signifies a substantial shift in our interaction with AI systems. As these models advance, the skill to communicate effectively with them becomes specialized. This shift, coupled with the growing integration of AI into business processes, underscores the need for skilled prompt engineers to ensure consistent, high-quality outputs.

Skills required

• Strong understanding of natural language processing and generation
• Familiarity with various AI models and their specific characteristics
• Excellent writing and linguistic skills
• Analytical abilities for performance evaluation and optimization
• Creativity for developing diverse and effective prompts
• Basic programming skills, particularly in Python
• Understanding of AI ethics and bias mitigation
• Data analysis and interpretation skills
• Problem-solving and critical thinking abilities
• Communication skills to collaborate with diverse teams

Suggestions to prepare for the role

• Experiment with AI: Explore a variety of AI models and platforms to gain practical experience. Some examples include large language models like OpenAI GPT, Gemini, and Claude and small language models like Phi3, LLama-3, and Minstral. These widely used models can be a great starting point for your exploration.
• Study linguistics: Deepen your understanding of language structure and semantics. This knowledge is essential for crafting prompts that effectively guide AI systems in generating coherent and contextually relevant outputs.
• Learn about AI/ML: Take courses or pursue artificial intelligence and machine learning certifications.
• Practice creative writing: Develop your ability to craft clear, concise, and compelling language.
• Engage with the community: Participate in online forums, attend conferences, and network with professionals in the field.
• Develop technical skills: Learn basic programming and data analysis techniques.
• Stay informed: Keep up with the latest developments in AI and prompt engineering techniques. This is not just a suggestion but a necessity in the ever-evolving field of AI.
• Build a portfolio: Document your prompt engineering projects and their outcomes.
• Ethical training: Educate yourself on AI ethics and responsible AI practices.

AI-Human Collaboration Specialist

With advancing AI technologies, organizations realize that maximizing productivity and innovation involves creating synergistic relationships between humans and AI. This shift reflects a new approach to AI integration, enhancing human capabilities rather than replacing human workers with AI.

This change has resulted in a demand for experts to develop, implement, and enhance workflows that maximize AI and human workers' strengths. These specialists work to bridge the divide between technological capabilities and human expertise, ensuring that integrating AI leads to improved outcomes rather than disruption or inefficiency. They promote effective communication and collaboration among AI developers, end-users, and management. Additionally, the AI-human collaboration specialist addresses the human aspect of AI integration, which includes change management, training, and managing concerns related to job displacement and AI reliability.

Skills required

• Strong understanding of AI capabilities and limitations
• Knowledge of human-computer interaction principles
• Expertise in workflow design and process optimization
• Change management and training skills
• Data analysis abilities for performance evaluation
• Strong communication and interpersonal skills
• Problem-solving and critical thinking abilities
• Understanding of various industry-specific processes and needs
• Basic technical skills to work with AI systems and tools
• Knowledge of ethical considerations in AI deployment

Suggestions to prepare for the role

• Empower yourself with AI knowledge: Enroll in courses or pursue AI and machine learning certifications to understand the technology's capabilities and limitations deeply. This knowledge will be your key to unlocking the potential of AI-human collaboration.
• Understand the human side: Dive into cognitive psychology, ergonomics, and human-computer interaction to understand how humans interact with technology. This empathy will guide your decisions in AI-human collaboration.
• Master process optimization: Study methodologies like Lean, Six Sigma, or Agile to become proficient in designing and improving workflows. These skills will make you a valuable asset in AI-human collaboration.
• Gain practical experience: Seek opportunities to engage in AI integration or process enhancement projects.
• Enhance communication skills: Practice explaining complex technical concepts to non-technical audiences.
• Change management: This is a critical skill for AI-human collaboration specialists. It involves understanding change, how people react to it, and how to guide organizations through technological transitions. This skill is essential for ensuring smooth AI integration and minimizing disruption.
• Stay informed: Keep up with the latest AI, robotics, and automation developments across various industries.
• Develop a multidisciplinary network: Connect with professionals in AI, human resources, operations, and other relevant fields.
• Gain industry-specific knowledge: Understand the unique challenges and opportunities for AI-human collaboration in different sectors.
• Practice ethical thinking: Familiarize yourself with ethical guidelines for AI deployment and consider the societal implications of AI integration.

AI-Enhanced Creativity Mentor

The AI-enhanced creativity Mentor role is focused on maintaining the human essence of creativity, leveraging AI in fields such as visual arts, music, writing, and design to guide creative individuals and teams in harnessing the power of AI to augment and enhance their creative processes rather than replace them.

Many artists and creative professionals are intrigued by and apprehensive about AI tools, creating a demand for mentors who can bridge the gap between traditional creative practices and cutting-edge AI technologies. These mentors can help demystify AI, showcase its potential as a collaborative tool, and help creatives integrate AI into their workflows in ways that amplify their unique artistic voices.

Furthermore, as organizations in creative industries seek to stay competitive and innovative, they recognize the need for specialists who can foster a culture of AI-enhanced creativity. This role also helps in skill development and navigating the ethical and copyright implications of AI-generated content, ensuring that the use of AI in creative processes aligns with industry standards and legal requirements.

Regardless of the industry, we all fundamentally need to express our creativity. The AI-enhanced creativity Mentor can help humanize the symbiotic relationship between humans and AI, enabling a collaborative environment where technology enhances our creative expression.

Skills required

• Strong understanding of various generative AI tools and their applications in creative fields
• Expertise in one or more creative disciplines (e.g., visual arts, music, writing)
• Ability to teach and mentor others effectively
• Knowledge of creative software and digital tools
• Understanding of copyright laws and ethical considerations in AI-assisted creativity
• Problem-solving skills to address unique creative challenges
• Excellent communication skills to explain complex AI concepts to creative professionals
• Adaptability and willingness to continuously learn about new AI technologies
• Project management skills to guide AI-enhanced creative projects
• Ability to analyze and interpret AI-generated outputs in a creative context

Suggestions to prepare for the role

• Gain hands-on experience: Have practical experience with various generative AI tools in creative fields.
• Develop your own creative skills: Stay active in your chosen artistic discipline(s).
• Continuous Learning: Take courses or obtain certifications in AI/machine learning and creative technologies.
• Be Curious: Experiment with integrating AI into your creative process to gain firsthand experience and stay informed about the latest developments in AI for creative applications by following relevant publications, conferences, and thought leaders.
• Build your portfolio: Showcase AI-enhanced creative projects and your ability to mentor others.
• Coach people: Develop teaching and mentoring skills through workshops, tutoring, online courses, and practice.
• Build your personal brand: Engage with online communities focused on AI in creative fields to share knowledge and stay updated.
• Ethics: Learn about the ethical implications and legal considerations of using AI in creative work.

Digital Detox Consultant

The Digital Detox Consultant role is of utmost importance in the current scenario, as it responds to the escalating apprehension regarding digital overload and its ramifications on mental well-being, productivity, and overall welfare. This position can assume a pivotal significance in the contemporary landscape due to the pervasive integration of digital technology in personal and professional life, giving rise to issues such as digital dependency, dwindling attention spans, and an imbalance between work and personal life.

As society becomes increasingly aware of the negative effects of excessive screen time and constant connectivity, this role holds the potential to guide individuals and organizations in developing healthier relationships with technology. The COVID-19 pandemic has further accelerated this trend, with remote work and increased reliance on digital communication exacerbating issues of digital overwhelm.

Digital Detox Consultants address a critical need in our hyper-connected world by helping people find balance, improve focus, and enhance real-world connections while still leveraging the benefits of digital technology. This role is not just about addressing issues, but about promoting digital wellness, becoming as important as physical and mental wellness in modern society.

Skills required

• Strong understanding of digital technologies and their impact on human behavior
• Knowledge of psychology and behavioral change techniques
• Familiarity with productivity tools and methodologies
• Excellent communication and coaching skills
• Ability to analyze digital usage patterns and their effects
• Understanding of ergonomics and its relation to digital device use
• Knowledge of mental health issues related to technology use
• Project management skills for implementing organizational changes
• Creativity in developing engaging offline activities
• Familiarity with mindfulness and stress-reduction techniques

Suggestions to prepare for the role

• Behavioral Science: Study psychology and behavioral science, focusing on digital behavior and addiction.
• Professional Certification: Gain digital wellness, mindfulness, or life coaching certifications.
• Platform Expertise: Deeply understand various digital platforms and their engagement mechanisms.
• Personal Practice: Practice and master different digital detox techniques personally to gain firsthand experience.
• Research Awareness: Stay informed about the latest research on the impacts of technology on health and productivity.
• Corporate Experience: Gain experience in corporate environments to understand workplace digital challenges.
• Data Analysis: Develop skills in data analysis to measure and track digital usage patterns.
• Ergonomic Knowledge: Learn about ergonomics and how to create healthier physical setups for digital device use.
• Professional Networking: Network with professionals in related fields like occupational health, HR, and IT.
• Brand Development: Create and maintain a personal brand that embodies digital balance and wellness.
• Presentation Skills: Gain public speaking and workshop facilitation skills to effectively present ideas to groups.
• Productivity Tools: Familiarize yourself with various productivity methodologies and tools supporting digital wellness.

My Final Thoughts

The revolution in AI work is not just about fancy titles: it is an attempt to keep our humanity intact in step with technology. We eventually invent roles like 'ethical AI manager' and 'digital detox consultant' to protect ourselves from our creations. It is curious, to say the least.

We are not only changing how we work but also redefining what it means to be human. The 'AI-Enhanced Creativity Mentor', a role that guides individuals in using AI to enhance their creative processes, highlights the need to maintain our creative edge in favor of algorithms.

In this brave new world, adaptability is not just a nice thing; it is survival. Tomorrow's jobs will require a blend of technological skills, such as coding and data analysis, and human characteristics, like creativity and emotional intelligence. As we navigate this AI-driven landscape, let us remember that authentic humanity may be our strongest asset.

Everything presented here is based on my personal experience and extensive discussions with colleagues, customers, and partners over the past two years. Regardless of the specific job titles and skills mentioned, I intend to provoke thought and discussion about the future of work in an AI-driven world. These are not definitive predictions but rather a snapshot of the evolving landscape as I've observed it. I hope this serves as a starting point for further reflection and conversation about how we can best prepare for the challenges and opportunities that lie ahead.