LinkedIn Scales Back AI Prompts Displayed to Premium Users
According to a Fast Company report, LinkedIn is silently removing the AI prompt suggestions in the feed which were spotted frequently by Premium users. These prompts appeared underneath every post and suggested related queries that a user could ask the AI. This feature was similar to what Meta released on Facebook.
However, the visibility of these prompts has reportedly been reduced significantly. LinkedIn spokesperson Suzi Owens confirmed to the publication that these AI suggestions were indeed being scaled back by the company, but highlighted that this was not in response to criticism by users or a negative perception of the AI features.
Members can still use our AI-powered tools on the jobs home page to get personalized insights, like how to build a network, position yourself for a job, or learn about a company,” the spokesperson told the publication.
The point about user criticism comes as several users reportedly found their feed bombarded by these prompts, and not helpful. These suggestions were meant to encourage users to try out the AI features the company launched in November 2023. Notably, there is no way to turn off these prompts on LinkedIn.
The Microsoft-owned platform recently faced criticism for training its AI models without telling its user base explicitly. The data collection reportedly same to surface when several users found a setting options to turn off data collection to train AI models. Soon after, the company updated its policy to reflect its decision to collect user data.
LinkedIn is rolling out several new artificial intelligence (AI) features to assist users in job search and personalized learning on the platform. Announced on Thursday, these AI-powered features include a Jobseeker Coach that can hunt the right job for users from a text prompt, a tool to review resumes and applications, and a chatbot that can interactively assist in creating cover letters and help in seeking professional advice. These features are being rolled out globally for the platform’s premium users. Read more
Key trends include Augmented Working, where AI and humans will collaborate more effectively. In 2025, businesses will move beyond just adding generative AI features and focus on leveraging AI to enhance human skills. This approach will free up employees to focus on creative and interpersonal tasks that AI cannot yet handle, creating real value for companies.
Real-Time Automated Decision-Making will also be a defining trend. As companies develop more mature AI strategies, they will automate entire business processes, particularly in logistics, customer support, and marketing. Algorithms will manage tasks like inventory control and customer inquiries with minimal human input, resulting in greater efficiency and faster responses to changing market demands.
Responsible AI will take center stage as businesses and governments push for ethical, secure, and transparent AI deployment. In 2025, organizations that ignore the risks of AI bias or misuse will face backlash from both regulators and the public. Ensuring that AI is used responsibly will become essential for businesses to maintain trust and avoid reputational damage. Read more.
LVMs revolutionize quality control by learning from specific data to quickly and accurately detect defects in products, reducing the time-to-market and ensuring quality standards are met consistently. These models surpass traditional methods, especially in complex tasks like distinguishing defects in raw materials or semiconductor wafers, setting a new standard for quality control.
For successful AI integration, organizations need a comprehensive strategy. First, embrace change management by preparing the workforce and fostering a culture of continuous learning and innovation. Engaging all stakeholders ensures everyone is aligned with the benefits AI brings to operational efficiency and product quality.
Next, start with pilot projects to test AI’s effectiveness in a controlled environment. By setting measurable goals, such as reducing defect rates, organizations can refine their strategies before expanding AI across other areas.
Finally, secure quick wins to build momentum. Implementing small, swift projects, like automating routine inspection tasks or using AI for real-time defect detection, demonstrates the value of AI and boosts support for larger initiatives.
By strategically incorporating AI, organizations can streamline operations, improve productivity, and enhance customer satisfaction. As AI evolves, continuous evaluation and adaptation are essential to maintain a competitive edge and ensure consistent product quality. The future of quality control lies in embracing AI for smarter, more efficient processes. Read more.
As businesses rapidly adopt AI technologies, the need for specialized AI skills has skyrocketed. Interestingly, job roles related to ML and AI are expected to grow by 16% through 2028, according to the US Bureau of Labor Statistics. These stats point out the possibility of AI being the dominant one amongst top career paths in the next ten years.
Considering the change, many professionals have already engaged in vocational programs and certifications for upskilling to thrive in the job market. Why should you be left behind? Let’s dive in to learn more.
The Career-Boosting Power of An AI Certification Course
Earning an AI certification is not just an addition to your CV, but a powerful tool to skyrocket your career. You not only stand out from the competition, but it shows your dedication towards continuous learning. Here’s what you have in hand after you become a certified AI practitioner.
Professional Credibility
AI certification is a proof of credibility and commitment that focuses on technical aspects and validates your knowledge and expertise about AI algorithms, applications, and concepts. When you have a solid understanding of AI principles, you become an asset for any organization.
However, it also depends on the training program from where you obtain the badge. Make sure you earn a certificate from a reputed training center or the industry giants.
Increased Job Opportunities and Advanced Roles
AI will create 133 million jobs by 2030, which will expand career prospects in various industries. AI certification shows your expertise and opens the door for opportunities for varied roles and responsibilities. AI practitioners naturally attract businesses who want AI experts to fill important roles.
Moreover, it serves as a pathway to climb up the ladder and present yourself for advanced roles or leadership positions.
Stability and Long-Term Growth
With a projected market size of US$305.90bn in 2024 worldwide, AI seems to be the driving force behind work transformation. This points out career advancement, stability, and long-term growth.
If you are planning career growth understand the growing market size, areas of demand, and career trajectory, and then quickly move with an AI certification.
Not just the data scientist, but anyone who is a certified AI practitioner do enjoy huge financial returns. However, your remuneration depends on your experience and location of work, but businesses place a higher value on certified expertise.
Networking Opportunities
A strong professional network is important for career growth. Gaining an AI certification can make you a part of a sprawling network of AI professionals. You will get an opportunity to connect with leaders in the AI space, participate in discussions, attend conferences, and sometimes lead AI-focused groups.
Staying Abreast with AI Trends
An AI certification keeps you updated with the latest developments in the AI landscape because the content aligns with the current industry trends. A well-rounded content balances theoretical knowledge and practical application, which enhances employability.
Exploring Career Paths for Certified AI Practitioners
The presence of AI can be felt in every industry. Whether you are a techie or a healthcare professional, a financial analyst or a media person, everybody is curious to know the actual application of AI in a real scenario.
Earning an AI certification could be a step towards career progression. However, you need a combination of technical knowledge and soft skills to succeed in the AI job market. But one should be prepared for the massive shifts across industries for career advancement. Here are a few career paths one can embark on as an AI practitioner.
AI Research Scientist
AI Consultant
NLP Engineer
AI Prompt Engineer
AI Architect
Research Scientist
Business Intelligence Developer
Machine Learning Engineer
AI Project Manager
Data Scientist
Data Analyst
Robotics Engineer
Key Takeaways:
AI is in high demand; upskilling can open doors for a promising career
AI certification boosts credibility with organizations placing trust in certified AI practitioners
Attract potential employers, high package salaries, stability, and growth with an AI certification
Expand your network as a certified AI practitioner and experience long-term growth
Choosing the Right AI Certification
AI certification is more than a magic bullet that paves the way for career advancement. But choosing the right certification program is pivotal. Consider the AI program’s relevance to your career goals, reputation, and curriculum according to the latest industry trends. Make sure the AI certification program you choose offers practical exposure and a growing community of industry experts to connect and work with.
Becoming a certified AI practitioner is not only a way to seek career growth but an opportunity for personal development as well. If you want to position yourself as the leader, push yourself a little farther and focus on getting an AI certification.
AI CERTs™ offer training programs for professionals in varied areas. Consider checking our AI certifications and lead the way.
Contact us to discuss your needs, we will help you navigate the job market successfully.
AI is experiencing an unprecedented growth spurt, revolutionizing daily tasks and even surpassing human capabilities in specific domains. From personalized experiences to supercharged efficiency and productivity, AI’s impact is undeniable. It automates repetitive tasks and harnesses the power of pattern recognition for predictive analysis, demonstrably improving our lives. The potential extends far beyond convenience, with AI poised to tackle societal challenges in areas like green energy and healthcare advancements.
Considering all the above factors, the global AI market is expected to reach USD 1.81 trillion by 2025, according to Statista which indicates increased adoption of AI in the coming time.
Moreover, AI’s capabilities to store, organize, and analyze vast data have also attracted businesses at large and they are all set to unlock valuable intellectual property. Interestingly, 70% of businesses who were surveyed by McKinsey & Company have already adopted or are in the process of adopting AI in some form.
Overcoming Hurdles- Challenges in Securing Employee Confidence in AI
Many organizations resist using AI considering the market full of AI vendors and varied technologies. There are concerns of job loss that have adversely affected the job market. You can sense the buzz with talks of AI LLM models like ChatGPT or Bard taking over the market. Thus, 72% of Americans are concerned about potential negative impacts like job loss and privacy according to a survey by Pew Research Center.
Additionally, ethical concerns like biased AI algorithms, potential misuse, and data privacy hinder decision-making processes. A recent study by the Algorithmic Justice League revealed that 38% of AI systems showed significant bias, which brings our focus to AI transparency which we have discussed in the section below.
AI Transparency – Understanding the AI Trust Gap
Our inherent curiosity compels us to seek explanations. Like a child’s relentless “why” questions, humans require understanding to engage effectively. This need for explanation extends beyond mere comprehension; it serves a critical role in our long-term survival.
Building trust in AI presents a similar challenge, fueled by ethical concerns and personal security anxieties. Businesses struggle to win over their workforce’s confidence in AI capabilities. The key lies in fostering transparency. When employees understand the inner workings of the AI system and how it arrives at decisions, it fosters not only transparency but also a sense of predictability and control. This empowers employees to trust AI and embrace its potential.
Building trust within a team, even among humans, takes time and effort. Extending trust to AI systems, whose inner workings are often opaque, presents an even greater challenge. A thorough understanding of these systems is crucial. By developing expertise in AI, we can bridge the gap and foster a collaborative environment where humans and AI work together seamlessly.
A Framework for Ethical AI Deployment
After knowing AI challenges and concerns and why teams lack confidence in AI, businesses should opt for planned evaluation, governance, and smart AI communication strategies. A strategic framework can address challenges and facilitate ethical AI deployment that includes:
AI Transparency
It is crucial to build trust in AI enabling transparency when AI is deployed, considering its usage, decision-making process, potential opportunities, and risks associated with it.
Robust Governance
Implementing robust governance structures and controls to mitigate risks and ensure responsible AI adoption. This includes ensuring data quality, safeguarding against unintended bias, and designing controls in the development process.
Partnership and Collaboration
Partnering with the right vendors who prioritize responsible AI practices and actively collaborate across the organization to build AI expertise.
Communication and Public Engagement
When it comes to AI communication strategies, proactively talking about AI initiatives is important. Make sure you explain the purpose of AI implementation and encourage the workforce to come up with their concerns.
AI in Organizational Trust- Key Considerations
A Gartner report predicts a staggering 7.4 million global talent shortage in AI by 2026. This highlights the critical need for increased investment in AI education and training programs. However, before diving headfirst into training, there are key considerations that pave the way for successful and trustworthy AI implementation:
Alignment: First, ensure your AI initiatives are tightly aligned with core business goals. This strategic alignment saves time, effort, and resources while streamlining operations for maximum impact.
Building Trust Through Transparency: Transparency is crucial for building employee confidence in AI. By providing an “inside-out” view of how AI reaches decisions, organizations foster trust. Easy-to-understand processes not only facilitate internal audits but also address evolving regulatory requirements, further building trust in AI systems.
Legal Compliance and AI: Remaining abreast of evolving regulations and ensuring AI platforms adhere to relevant legal frameworks is vital. This demonstrates responsible AI development and helps build trust with stakeholders both inside and outside the organization.
Governance and Expertise: Finally, consider organizational structures that support successful AI integration. This includes establishing dedicated AI governance teams and embedding data science expertise throughout the organization. These measures ensure responsible and effective AI deployment.
By addressing these key considerations, organizations can navigate the talent gap, build trust in AI, and unlock the tremendous potential of this transformative technology.
Key Takeaways
AI is rapidly growing owing to its capabilities but still not accepted and people are resisting use because of trust issues.
AI increases efficiency, improves productivity, offers personalization, and aids decision-making, but has various ethical concerns like biased algorithms, fear of job loss, data privacy, and potential misuse that hinder trust and wide acceptance of AI.
AI transparency including the inside out of its working will make people feel comfortable and confident using it.
Responsible AI deployment requires strategic communication and framework to ensure transparency, ethics, robust governance, collaboration with responsible vendors, and proper alignment with business goals.
Building a Responsible AI Future
AI undoubtedly holds great power, but its successful application hinges on responsible development and implementation. Businesses can harness the immense potential of this technology while mitigating associated risks and building trust in AI. It is crucial to prioritize trust, transparency, and AI ethics, to contribute to a better future.
As AI is the most talked about subject in the corporate world, owing to its both negative and positive sides, it has become the most sought-after career domain. Businesses wanting AI experts have made it the skill of the century. Getting a certification in AI will not only help you challenge the traditional way of working but will establish you as a leader in the domain.
How frequently have you heard these inquiries, or ones like them? “Recently, our rival released new features. Could you please replicate it right away?” “Our application has included AI and ML. When can you finish it?” “This month’s conversion rates are low. Can you take immediate action to make them better?” “The cost of this method is excessive. Is it possible to automate it?” A constant gap exists in businesses between technology, operations, sales, customer service, marketing, and finance, often due to conflicting priorities, communication issues, and disparities between immediate and long-term objectives.
What is the Business-Tech Divide?
The business-tech divide refers to the gap between business expectations and technical realities within organizations, often exacerbated by differing priorities, communication breakdowns, resource constraints, and a disconnect between short-term goals and long-term strategies. Bridging this gap is crucial for ensuring organizational resilience and adaptability in an evolving digital landscape. As the digital divide continues to evolve, a new dimension emerges: the AI divide, which affects organizations and individuals in distinct ways. Those who proactively integrate AI with a clear understanding can navigate change effectively while ensuring business continuity. In today’s corporate environment, establishing high-performance teams that leverage AI capabilities is indispensable for achieving success. Such teams not only enhance collaboration and productivity but also drive superior outcomes. To harness AI effectively, organizations must first grasp its fundamentals, set precise business goals, foster open communication, and enhance data literacy. Additionally, empowering AI teams and engaging in ethical discussions are pivotal for responsible AI use.
Building a High-Performing AI Team
• Defining Objectives: Clearly define the project’s objectives and desired business outcomes to ensure alignment with the business strategy. • Role Identification: Identify the necessary experts and professionals required for effective project execution. • Recruitment and Training: Hire, outsource, or upskill existing employees to fill the identified roles. • Collaboration and Communication: Establish robust communication channels to facilitate idea sharing and efficient issue resolution. • Monitoring and Continuous Learning: Use performance indicators to track progress and identify areas for improvement. • AI Model Analysis: Regularly analyze the performance and effectiveness of AI models, making appropriate revisions to measure their impact on business objectives.
Collaboration in B2B AI Projects
AI has revolutionized project management by enhancing team collaboration and planning. By integrating AI capabilities into collaborative systems, workflows can be optimized, costs reduced, and on-time delivery increased. AI automates routine tasks, predicts risks, and facilitates communication, enhancing teamwork and performance analytics. AI-powered task assignment and resource allocation eliminate guesswork, allowing for optimized workflows and faster project delivery. AI-powered project planning and scheduling generates efficient plans and schedules, balances priorities, and identifies ways to reallocate resources. This technology empowers project teams to work smarter, making AI-driven collaboration essential for successful delivery.
How to Create an Innovative Culture in B2B AI Development
The integration of AI in the workplace requires strategic leadership to cultivate a culture of learning and innovation, fostering an environment that encourages curiosity, acceptance, and the development of soft skills
Senior executives must lead the way in embedding AI into the organization’s DNA, demonstrating a genuine commitment to its future. All levels of leadership should participate actively in AI initiatives, with departments exploring generative AI tools for frontline roles and coding AI platforms for tech-focused teams. Regular training, incentivized skill development, and one-on-one mentoring and coaching are essential for all departments to engage with AI in a manner that makes sense for their roles.
Case Studies: Successful AI Team Configurations
AI team configurations can boost team performance by predicting interpersonal affinity and reproducing the precision of a psychologist’s analysis. Successful AI team configurations include Google DeepMind’s 30% reduction in data center costs and Pfizer and BioNTech’s collaboration on COVID-19 vaccine development. AI algorithms help identify potential vaccine candidates, conduct simulations, and optimize clinical trials, resulting in a safe and effective vaccine.
Takeaways
The gap between technical reality and business expectations, known as the “business-tech divide,” can be bridged by high-performing AI teams and flexible digital infrastructures.
Learn the fundamentals of artificial intelligence, establish clear corporate goals, promote open discourse, increase data literacy, empower the AI team, and engage in ethical discussions.
High performing team practices include defining objectives, identifying expertise, hiring, and upskilling personnel, encouraging communication, monitoring, learning, and assessing outcomes.
Implementing successful techniques, such as developing team cooperation, streamlining workflows, improving cost management, and prioritizing on-time delivery, adds to these good results for building a high performing team.
Conclusion
Continuous learning is crucial for building high-performing AI teams. AI can revolutionize team operations by providing valuable predictions and analysis, enabling teams to identify critical patterns and behaviors for success.
Bridge the gap between technical and business stakeholders in B2B environments to create high-performing AI teams by enrolling in the AI+ Project Manager™ certification.
