AI will transform 92% of ICT jobs, with significant impacts on entry and mid-level positions.,Seven job families will be most disrupted, including business and management, and design and user experience.,Workers must acquire new skills like AI ethics, prompt engineering, and machine learning to stay relevant.
Artificial Intelligence (AI) is not just the future; it's the present. It's transforming jobs, and the tech giants are taking notice. According to a bold new prediction, more than 92% of information and communication technology (ICT) jobs will be highly or moderately transformed by AI. This change is inevitable, and we must prepare for it. Let's dive into the details.
The AI-Enabled ICT Workforce Consortium
The AI-Enabled ICT Workforce Consortium, formed by tech giants like Google, IBM, Microsoft, and others, has released a comprehensive report, “The Impact of Generative AI.” Ryan Oakes, global health and public service industry lead at Accenture, said, “Gen AI has the potential to reinvent fundamental aspects of our daily lives. We are tackling the opportunities and challenges that the workforce will face as generative AI becomes increasingly prevalent.”
Seven Job Families to Be Most Disrupted
The consortium analyzed 47 specific ICT job roles across seven job families. These families include business and management, cybersecurity, data science, design and user experience, infrastructure and operations, software development, and testing and quality assurance.
Business and Management
In business and management, 62.5% of roles were identified as high transformation and 37.5% as moderate. AI can help create product strategies, provide predictive analytics, develop reports, manage large-scale projects, and automate numerous processes.
Skills to Acquire:
AI-driven competitive analysis,AI integration strategies,Machine learning (ML) literacy, Prompt engineering,Data science and visualization,Natural language processing (NLP)
Skills with Decreased Relevance:
Basic data analysis,Manual data cleaning and preparation,Task scheduling,Basic report generation,Documentation maintenance,KPI monitoring
Design and User Experience
In the design and user experience family, 66.7% of roles are expected to have high transformation and 33.3% moderate transformation. AI can automate routine tasks, streamline workflows, facilitate data analysis, and create “hyper personalization.”
Skills to Acquire:
Machine learning (ML),Prompt engineering,Proprietary AI design,Scikit,Data analysis and interpretation,Product design,Lean manufacturing
Skills with Decreased Relevance:
Basic coding,Manual content creation,Research
Skill Shifts Require Quick Action by All Parties
The consortium identified 10 increasingly relevant skills:
AI ethics and responsible AI,AI literacy,Prompt engineering,Large language model (LLM) architecture,Agile methodologies,Data analytics,Machine learning (ML),Retrieval augmented generation (RAG),TensorFlow,Natural language processing (NLP)
On the other hand, the 10 technical skills expected to decrease in relevance include:
Basic programming and languages,Content creation,Data management,Research information,Documentation maintenance,SQL,Manual XML handling,Manual Perl scripting,Integration software,Manual malware analysis
What Enterprises, Academic Institutions, and Workers Must Do
Enterprises must invest in AI training to promote competitiveness and innovation. They should attract and retain talent while considering worker training needs and feedback.
Academic Institutions should update their curriculum to include AI technologies and offer concise certificate programs. They should prioritize investments in work-based learning initiatives, flexible learning paths, and collaboration with regional secondary education institutions.
Workers must “embrace lifelong learning to stay relevant.” They should proactively seek reskilling and upskilling opportunities through employer programs, labor-sponsored training, online courses, or certifications. Those just joining the workforce can take advantage of internships, mentorships, and hands-on projects.
The Future of AI in the Workforce
The consortium plans to explore public-private partnerships to contribute to an “AI skills taxonomy” that will define and map skills to roles and define required levels of proficiencies. They also plan to introduce an AI Workforce Playbook to help enterprises of all sizes proactively reskill and upskill workforces.
Francine Katsoudas, EVP and chief people, policy and purpose officer at Cisco, said, “AI represents a never-before-seen opportunity for technology to benefit humankind in every way, and we have to act intentionally to make sure populations don’t get left behind.”
Comment and Share
What AI skills are you most excited to learn? How do you think AI will transform your job? Share your thoughts in the comments below and Subscribe to our newsletter for updates on AI and AGI developments.
Latest Comments (3)
The Consortium's finding that business and management roles face 100% transformation (high or moderate) resonates with our discussions on ASEAN digital integration. We see AI integration strategies and ML literacy as crucial for public sector efficiency, aligning with our national digital economy roadmap.
this 92% transformation figure... it really resonates with what we're seeing internally, especially for the "business and management" roles they mentioned. we're trying to push AI tools for things like competitive analysis and predictive analytics for our product strategies, but the compliance hurdles are insane. every new model needs endless approval. so yeah, "AI integration strategies" is definitely a skill we need, not just to build but also to actually deploy within a regulated environment. it's a whole different beast when you're not a startup. gotta keep pushing though.
@harryw The report mentions prompt engineering as a key skill, but it feels like the current debate in academia is whether that's a temporary skill or a foundational one. Are we seeing a shift towards more abstract model interaction, or will "prompt engineering" evolve into something more akin to domain-specific language mastery?
Leave a Comment