What if you gave AI your current job profile and asked it to predict what your work could look like a year from now? Would it simply repeat the skills you already have, or identify capabilities you may need to build before they become important?
I wanted to test that for myself. I gave ChatGPT details about my professional experience, current responsibilities and skills, and asked it to assess where I stood today. I then asked it to identify the gaps in my profile and predict what my work could look like 12 months from now.
I wanted to know what skill do I need to learn and demonstrate to remain competitive in my field a year from now?
Where does my profile stand today?
My first prompt to ChatGPT was to assess my professional profile against journalists and editors with around five to eight years of experience at established digital publications.
I wanted an honest assessment, so I specifically asked it not to be encouraging for the sake of it. ChatGPT described my profile as a “strong editorial operator + increasingly capable reporter/writer + early-stage AI user + underdeveloped audience/product/data/visual-video skill set.”
Its assessment gave me a mix of strong areas and clear gaps:
- Core editing and newsroom experience: 8/10
- Exclusive and in-depth reporting: 7/10
- Interviewing and source communication: 7/10
- International/US news: 7/10
- AI/LLM usage: 5/10
- SEO: 5/10
- Audience analytics: 3/10
- Data journalism: 2/10
- Video and short-form journalism: 2–3/10
- Social distribution: 3/10
- Digital product thinking: 2/10
The assessment was not that I lacked journalism experience. In fact, ChatGPT said the opposite. Its concern was that my experience and my current digital skill set were not developing at the same pace.
It described the next stage as moving from being a reliable newsroom professional to becoming a more specialised digital editorial professional.
What skills could matter more in 2027?
I then asked ChatGPT to identify the skills I should prioritise instead of simply giving me a long list of courses. It divided the gaps into three broad levels.
The most important and urgent skills were:
- Data literacy: Moving from Excel and Sheets towards data analysis, visualisation and eventually SQL or Python.
- Audience analytics: Understanding GA4, Search Console, publisher analytics and using audience behaviour to inform editorial decisions.
- Video and social storytelling: Developing skills in vertical video, YouTube and other formats beyond traditional articles.
- Advanced AI for journalism: Moving beyond basic prompting towards research workflows, automation, structured AI systems and agents.
It placed OSINT and investigative research, AEO/GEO, multimedia storytelling, newsletter development and basic no-code automation in the next tier. Editorial strategy, project management, mentoring, product thinking and understanding newsroom economics would become more important for people moving towards senior editorial or strategy roles.
ChatGPT suggested that I add new layer of skills in addition to the ones I have mastered.
What could my job look like a year from now?
I then asked ChatGPT to turn those gaps into a 12-month development plan. Its central idea was that learning a skill is not enough. I should be able to show what I can do with it.
The first stage would focus on building AI-assisted research and reporting workflows. Instead of using AI mainly for drafting, editing or brainstorming, I would use it to analyse documents, compare information, assist with research and make repetitive newsroom tasks more efficient.
The next stage would introduce data. ChatGPT suggested taking a real dataset, cleaning it, finding a meaningful pattern and turning that finding into a journalistic story.
Later, I would add audience analytics, OSINT and multimedia skills.
The progression would look roughly like this:
- Early stage: Build repeatable AI-assisted research and reporting workflows.
- Next stage: Analyse real data and turn findings into story ideas or published work.
- Middle of the year: Add audience analytics and use performance data to make editorial decisions.
- Later stage: Combine AI, data, investigation and multimedia in original journalism.
- By 12 months: Have a portfolio showing capabilities that go beyond routine writing and editing.
The important part was that ChatGPT wanted each stage to produce something tangible.
It suggested that by the end of the year there should be “physical evidence of capability, not merely knowledge.”
That changed the way I looked at the plan. Instead of asking how many courses I could complete, the better question was what I could actually demonstrate after completing them.
What was the biggest warning AI gave me?
The most uncomfortable part came when I asked ChatGPT to look beyond the skills I should learn and suggest what could happen to my professional value if I did not adapt.
Its answer was not that AI would simply replace journalists. The bigger risk, it said, was another journalist with similar experience but stronger AI, data, analytics, video and audience skills becoming more valuable.
Experience still counts, but years spent doing similar work do not automatically create a professional advantage.
ChatGPT said the industry is moving towards a model where generic text production becomes easier to automate, while original reporting, analysis, verification, video, AI capability and audience relationships become more valuable.
It also identified another problem. It stated I have a broad set of interests and skills, but not yet one clearly defensible professional advantage.
It suggested that, at this stage of a journalism career, I should begin building at least one area that I can own. That could be data journalism, investigative reporting, audience expertise, multimedia, AI-enabled journalism, a specialist beat or editorial leadership.
That was probably more useful than any individual course recommendation.
What worked, what didn’t?
ChatGPT was useful in making me think beyond the skills I use every day. It identified data, audience analytics, AI-assisted reporting, OSINT and multimedia as areas that could strengthen my existing journalism experience.
I also found the focus on building evidence rather than collecting courses useful. A data-driven story or an AI-assisted reporting workflow can demonstrate a new capability in a way that simply completing a course cannot.
But I would not treat the prediction as a definite picture of where my job will be a year from now. AI can identify possible trends and skill gaps, but it cannot understand exactly how a newsroom, audience or individual role will evolve.
The exercise was therefore less about predicting my future job and more about asking what I can do today to make my professional profile stronger a year from now.
For me, the biggest takeaway was that I do not need to learn every new AI or digital skill. I need to identify a few that complement my existing experience and turn them into capabilities I can actually demonstrate.
AI cannot tell me exactly what my job will look like in August 2027. But it can force me to ask whether the journalist I become by then is more capable and differentiated than the one I am today.
Disclaimer: This is a first-person experiment conducted for informational and entertainment purposes. Financial Express does not encourage or discourage any career decision or the use of AI tools for professional development and is not responsible for any decisions or professional consequences arising from the AI-generated recommendations discussed in this article. The skills, career assessments, predictions and other suggestions generated by AI are not guarantees and should be independently evaluated before being acted upon.