Six months ago I wrote a post called AI is coming for your services job which argued that many lower-skilled roles were at risk of automation. This is certainly proving to be true, but having met hundreds of companies since then, I believe it vastly undersells AI’s impact. As models have improved, AI has become highly proficient at reading, researching, summarizing, writing, extracting, speaking and listening. It can also mix and match these competencies. What’s clear is that AI will not just automate labor in lower-skilled jobs, but also many high-skilled and creative professions. It will radically reshape the skills required and the workforce dynamics of every industry.
As an investor this is extremely exciting stuff (but as a human, it’s scary) as I believe the next 5 years provides an unprecedented opportunity to transform virtually every industry. At 1984 Ventures, we have already made labor automation investments in categories like software engineering (Cline), medicine (OpenClinic), medical scribing (Deepscribe), recruiting (Apriora), sales prospecting (Bluebirds), debt collection (Collectwise) and AR collection (Stuut) - and are on the hunt for more.
Below, I share a running list of jobs and tasks whose core functions are already capable of being done by AI today. It’s important to state upfront that I don’t think these jobs will completely disappear. In many cases, the end state may be copilot tools that augment humans. In others, it will mean that humans predominantly review and curate the outputs generated by AI. Overall though, substantially fewer humans will need to be hired into the role going forward.
Jobs that will be automated
I’ll keep adding to this list over time - let me know if there are jobs that I’ve missed or opportunities that appear mischaracterized.
Job | Explanation | Example startups | Opportunity for startups |
Receptionist | Voice AI (TTS, ASR, LLM and latency) is quickly approaching parity with humans. It can welcome guests, (re)schedule appointments, update customer records and perform administrative tasks | Dodo (vet clinics), HeyLibby (gyms) | High:
many verticals still untapped |
QA tester | While the long tail of scenarios to be tested has been hard to automate, AI agents + computer use functionality provide a promising paradigm shift | Ranger | High:
largely untapped |
Marketer | SEO and SEM campaigns can be managed algorithmically using AI (choosing creative + copy, testing, updating, monitoring), opening up agency-level services to the mass market | Multiply (Google Ads), Cactivate, Agentio | High:
no clear winners as yet |
Debt collector | AI already has a 2-5x higher collections rate than collections agencies. It can automate both outreach (call/text/email) and legal enforcement | Domu (banks), CollectWise *(healthcare) | High:
largely untapped, clear ROI |
Real estate agent | Technically, most parts of an agent’s job (property discovery, listing, touring, market comps, transaction coordination) can be done by AI already. But given buying a house is the biggest purchase consumers make in their lives, it remains to be seen if they will become comfortable outsourcing this to AI | Modern Realty | High:
largely untapped, clear opp to undercut on commissions |
Travel agent | AI is capable of planning trips and once AI agents are further developed, will be capable of booking trips. Travel agencies will no longer limited to luxury, group or business travelers | Gazelle Travel | High:
largely untapped |
Recruiter | AI can already interview candidates across blue collar and white collar roles (and pick the same candidates as human recruiters). JD creation, candidate sourcing and scheduling can also be automated | Apriora* is conducting 1K+ interviews a week, Mercor | Medium:
many verticals untapped, but some emerging players |
AR rep | AR collections has many similarities to debt collections. AI can reduce DSO by automating outreach, correcting invoices, processing payments, managing cash and parsing remittances | Stuut*, Tabs, Tesorio | Medium:
already well funded category, but no clear leaders |
RCM rep | RCM companies use offshore call center teams to do things like insurance verification, prior authorization, credentialing, medical coding and billing. All of these can be automated. | SuperDial | Medium:
already v well funded category |
Call center agent | Voice AI can handle most call center queries | Thoughtly | Medium:
already v well funded category |
Paralegal | LLMs are perfectly suited to legal research and document generation. This has already become a hugely funded VC category because of the clear ROI | EvenUp automates the drafting and reviewing of personal injury claims | Low:
already v well funded category |
Medical scribe | AI medical scribes can already accurately perform the role of a human (listening to patient-doctor conversations, transcribing them and pushing relevant info to the EHR). They have already reached 90+% accuracy (which will trend towards 100%) and shave off 75% of time previously spent on documentation | Deepscribe*, Abridge | Low:
already v well funded category with strong players |
Customer support agent | Has been a huge area for VC investment. Still open questions on the automation of complex tickets, but lower level tickets are already being resolved by AI at a fraction of the cost of humans | Decagon, Sierra, Siena, Tymely (ecommerce) | Low:
already v well funded category |
Software engineer | Software engineering will change radically with the rise of AI coding assistants like Cline/Cursor. It’s unclear what this means for engineers long term, but the industry will certainly change a lot | Cline*, Cursor, Windsurf | Low:
already v well funded category with strong players |
Language tutor | You can hold a conversation with an AI language tutor that’s a fraction of the price of a human | Issen | High:
largely untapped |
What’s interesting is the breadth of jobs and skillsets. There are monotonous and repetitive jobs, creative jobs (e.g advertising) and also those we’d consider to be highly skilled (e.g. lawyer, software engineer).
Many of the high skilled jobs (e.g. doctor) are ones we’d normally call experts delivering advice. The paradox of AI is that experts are highly susceptible to automation because the corpuses of knowledge that underpin their expertise can be fed into LLMs. This has already happened with software engineering. It wouldn’t surprise me to see AI doctors, therapists, nutritionists and tutors in the coming five years. This will have the interesting effect of democratizing access to experts at a fraction of the cost, opening up markets that may have historically been priced out of such services.
Tasks that will be automated
Automation can also be thought of by task rather than job, with a task being something done across a number of jobs. My view is that tasks focused on research, content generation and code generation are already being made radically more efficient by LLMs. Some examples below.
Task | Explanation | Startups |
Drafting marketing proposals | AI can ingest and synthesize information from various sources and produce pitch decks | Henry (CRE), Joist (AEC) |
Report writing | Report writing and form filling (e.g. RFQ responses, security questionnaires) can already be automated | Sweetspot (govt contracting), Aptos |
Building MVPs | Using AI coding assistants you can build fully functional MVPs (frontend and backend) with natural language. No need for no-code! | Cline, Cursor, Create.xyz |
Website building | AI coding assistants commoditize the build of websites. Will democratize website building across any industry, including offline ones | Durable (home services), Framer (startups) |
Research | This is a huge category of investment, with AI proving that it can do legal, financial, business and market research (reading, synthesizing, summarizing). As context windows for models increase, more complicated/context interdependent research becomes possible | Bench IQ (legal), Quno (market) |
Sales prospecting | 100s of startups are building lead gen + automated outreach tools across many industries (B2B SaaS, construction, healthcare, financial advisory), automating a significant portion of the role of SDRs. These tools can research buyers, see if they fit within your ICP, automating outreach to them, and booking meetings with them | Clay, Bluebirds*, Unify |
A recent quote from Goldman Sachs CEO David Solomon highlighting AI’s content generation capabilities.
Advice for founders building labor automation startups
Just because a job can be automated doesn’t mean it will be an easy sell. Companies are often skeptical about whether a piece of software can fully mimic their human employees - and even if they can, they are typically reticent to fire large swathes of their workforce, even if it can impact their bottom line. Additionally, there is an inherent tension in asking employees to learn to use a new software tool that is being designed to eventually replace them.
Instead, it’s easier to position your product as augmenting humans rather than replacing them - turning them into 10x employees. It’s also easier to sell a solution that automates something that wasn’t previously being done (e.g. Revv sells auto shops software that does research on vehicle calibrations, a task that body shop technicians simply weren’t doing before, but is lucrative to do). Another alternative is to start by automating a task, rather than a job. This approach has the more subtle impact of reducing the need to hire for the role going forward (once the company realizes how much more efficient their employees are with the software), rather than asking the company to fire the staff upfront.
(Tagline from a website recently showing a good understanding of this nuance)
Conclusion (to add)
- Back office work in many industries will be completely restructured
- Repetitive workflows will be automated
- Many research tasks can be dramatically reduced
- Personal assistants for everyone across a variety of facets of life (e.g. personal shopper, EA to schedule, travel agent to book trips)
Travel agent
Personal shopper
Wedding planner
Life coach