Job Satisfaction, Work-Life Balance, Promotions, and More

☕️ Greetings, and welcome to my daily dive into the Generative AI landscape.

This newsletter is evolving with a goal to increase its value to the readers. You will continue to see structural changes in the coming days and your feedback is welcome.

Today’s issue covers the following:

• Job Satisfaction, Work-Life Balance, and Promotions, and more

• Seven reasons why generative AI will fall short in 2024

• Nearly 80% of British teenagers have used generative AI

• GenAI applications in cloud-native DevOps, particularly in microservices and Kubernetes, are extensive.

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♨️ TOP STORY

In Ireland, the adoption of artificial intelligence (AI) tools in the workplace is on the rise, with 28% of employees using AI to request promotions and 20% seeking raises, as revealed by research from Workhuman. Additionally, 22% have employed AI when resigning, citing increased productivity as a notable outcome. Generative AI tools like ChatGPT are playing a pivotal role in communication during these crucial moments.

Key Points:

• 28% of Irish employees use AI to request promotions, while 20% utilize it for salary increase negotiations.

• 22% have employed AI when resigning, experiencing productivity gains.

• 58% of Irish workers now use AI, with 38% doing so frequently.

• 47% use generative AI tools, like ChatGPT, for email drafting, and 44% for brainstorming.

• 50% of those who attempted to pass AI-generated work as their own were discovered.

• Happy employees are 64% more likely to use AI in their roles compared to unhappy ones (26%).

• 46% believe that AI adoption would increase job retention, while 71% expect improved productivity.

• AI is projected to enhance job satisfaction, work-life balance, and create new job opportunities, although 42% have concerns about job replacement.

• 88% of AI users in the workplace credit it with increased productivity, notably in workload reduction (49%) and decreased time spent on repetitive tasks (47%).

• Time saved by AI users is spent on socializing with colleagues (50%), assisting team members (46%), and tackling previously unmanageable tasks (42%).

• AI is making jobs easier (91%), improving job satisfaction (86%), and enhancing overall well-being (84%) for employees.

• AI adoption is seen as promoting workplace diversity (85%) and inclusivity (82%).

• Despite AI's increasing role, 20% of employees in AI-utilizing companies report no training in its use or application.

• Emphasizing the importance of maintaining the human element in AI integration, employers are urged to work with their teams to harness AI's benefits effectively.

Reference: How Workers Are Using AI To Get Promotions And Raises From Employers

🤝 B2B

In 2024, generative AI is expected to significantly transform B2B influencer marketing. As per industry experts, AI will enhance efficiency in identifying and selecting relevant influencers, tracking performance, and tailoring campaigns through precise audience segmentation. Emphasizing the integration of AI for content optimization, these advancements will reshape influencer marketing dynamics. AI’s ability to analyze data and generate content will enable brands to engage more effectively with niche markets, leveraging influencers to create impactful, personalized narratives. This evolution in AI technology underscores a shift towards more strategic, data-driven influencer collaborations in the B2B sphere.

Reference: Integral AI: 10+ Expert Insights On GenAI’s Ascent in B2B Influencer Marketing in 2024

📈 TRENDS

The rapid emergence of generative AI holds immense potential, but there are key challenges and pitfalls that may hinder its effective deployment in 2024. Insights from experts highlight seven critical reasons why generative AI might not meet expectations in the short term.

Key Takeaways:

1. Inadequate Query Formulation:

   • Companies may pose poorly structured questions, leading to plausible yet incorrect AI-generated responses.

2. Complex Model and Algorithm Selection:

   • The process of choosing and training AI models is intricate and often underestimated.

3. Bias in AI Training:

   • AI models may develop biases based on the data they are trained on, impacting their utility in diverse scenarios.

4. Misalignment with Business Needs:

   • Businesses might misapply AI models, using them for manipulation rather than genuine training, leading to misleading results.

5. Premature Organizational Changes:

   • Companies might hastily restructure, relying too heavily on AI, which could lead to operational inefficiencies.

6. Underestimation of AI's Complexity:

   • Businesses might overlook the sophistication required to effectively implement and benefit from AI.

7. Vendor Short-termism:

   • Vendors might prioritize immediate sales over long-term utility, causing businesses to invest in suboptimal AI solutions.

Advisory for Businesses:

• Approach AI with cautious experimentation in 2024, leveraging external expertise and focusing on verifiable, smaller data sets. Stay pragmatic, aware of the potential pitfalls, and prepare to adapt and learn continuously.

Reference: (GigaOm, 2023) Seven reasons why generative AI will fall short in 2024

🗣️ CULTURE

A study by Ofcom reveals that 79% of British teenagers (ages 13-17) and about 40% of children (ages 7-12) use AI tools, surpassing adult usage. Popular among teens are Snapchat's My AI and ChatGPT. The UK is increasing AI collaboration but treads cautiously on regulation. Daily internet usage in the UK has risen, with YouTube surpassing Facebook in popularity. The report also notes significant use of dating services, access to adult content, and experiences of online harms.

Reference: Nearly 80% of British teenagers have used generative AI

🔦 INDUSTRY SPOTLIGHT

Digital Domain, a pioneer in entertainment technology, has made significant strides in the generative AI sector, particularly in finance. At the 2023 Taipei International Financial Expo, they showcased "Generative AI in Financial Services," featuring advanced AI-driven virtual entities and collaborations with major banks like CTBC and Taishin International. Their innovative solutions include "Virtual Teller Rose & Sunny" and AI Assistants, offering personalized financial advice and user-friendly experiences. Digital Domain's CEO, Daniel Seah, emphasizes the symbiosis of technology and art in revolutionizing various sectors. This move marks a new era in financial services, blending AI with human-like interaction to enhance customer engagement and meet modern technological demands.

Reference: Technology Rooted in Humanity, Digital Domain Dives Into Finance Industry with Generative AI in Financial Services

🧰 TOOLS & APPS

AI Tools Directory: AI DIR Wiki

📦 USE CASES

Generative AI is revolutionizing software development, offering more than just code generation. Its applications in cloud-native DevOps, particularly in microservices and Kubernetes, are extensive. Key areas like code review, test generation, and operational planning can benefit from AI, enhancing efficiency. Challenges include balancing AI use with security concerns and choosing the right machine learning models. Despite hesitance due to risks, the growing adoption of AI in development processes is undeniable, with significant potential to streamline workflows and improve productivity.

Reference: Applying Generative AI Within Cloud-Native Workflows

👩‍💻👨‍💻 SKILLS & CAREERS

Telehouse's report reveals a substantial AI skills gap among UK IT decision-makers, with 29% acknowledging this deficit. A striking 63% note a pronounced lack of diversity within IT teams. The study, encompassing 250 IT leaders, identifies AI and data analytics as key future challenges. Businesses are countering this with internal and external training initiatives, while prioritizing diversity and inclusion efforts. The industry faces an urgent need to cultivate a more diverse talent pool and entice younger generations into technology roles to sustain innovation.

Reference: Britain’s Vision of Becoming a Global Innovation Hub Threatened by AI Skills Shortages and Lack of Diversity in IT

📚LEARNING

This article describes the process of building an AI assistant for business or personal use, outlining the key steps from conception to deployment. Emphasizing its transformative potential, it offers a roadmap for leveraging AI to improve efficiency, reduce costs, and enhance customer experience.

Key Steps:

1. Define Goals: Identify tasks and problems for the AI assistant to address.

2. Choose AI Platform: Select for ease of use, scalability, and system compatibility.

3. Develop AI Logic: Create responsive algorithms using machine learning.

4. Train the System: Update training data for continuous learning.

5. Design User Interface: Focus on intuitive and simple interaction.

6. Build and Test: Prototype, test with users, and refine.

7. Deployment: Implement with scalability, support, and documentation.

8. Monitor and Update: Continuously track and adjust post-deployment.

9. Collaborate with Experts: Partner with AI agencies for specialized needs.

10. Utilize AI's Benefits: Leverage AI for efficiency and enhanced customer experience.

Reference: How to build an AI assistant for your business or yourself

Related Video: (Liam Evans) How to Create a Personal AI Assistant

🔬 RESEARCH

The rapid evolution of AI is reshaping knowledge work, impacting daily and professional life. Emphasizing AI as a collaborative partner, not just a tool, requires maintaining human oversight. Lessons from aviation warn against over-dependence on automation, which can lead to reduced alertness and skill loss. Our proposed design approach promotes active human involvement and skill development, ensuring a balanced and empowering human-AI partnership. It's crucial to design AI interactions that prioritize human agency, with AI as a supportive co-pilot under human control.

Reference: (ArXiv, 2023) The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond

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