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One of the most common requests we get these days is Strategy Breakdowns articles focussed on AI strategy.

How are companies using AI today? What are they building to leverage in the near future? What is the strategic rationale behind these bets?

An often-heard counterweight to the AI revolution is: “The output just isn’t that good”. As of today, this is certainly true with respect to writing, editing, etc.*

^{* For readers from 10+ years in the future, when this seems like an unimaginable thing to say - the most advanced models at the time of writing are Claude 3 Opus, GPT-4o, Gemini 1.5 Pro, and Llama 3.}

A thesis I’ve been developing to identify which industries / companies / value chains / JTBD will definitely be disrupted by AI is:
Those revolving around things that AI is undeniably 10-100x better at than humans already.

2 characteristics instantly come to mind:

1. Processing speed: Sure, GPT-4o can’t write a 10/10 2000-word article. But it can write a 7/10 2000-word article in 5 seconds.

2. High-volume data ingestion: It might take a human ~2hrs to skim read and take notes from 20x sources. AI can ingest 200x sources in 5 seconds.

A low-hanging fruit to apply this principle to is supercharging scaled services businesses that are already successful. Why?

AI essentially transforms human services (labour and time-intensive) into tech products (automated, scalable, near-instant). It removes the ‘delivery’ element of certain tasks that could not previously be ‘automated’ in the traditional sense, but now they can.

Segueing into today’s article, last week I was lucky enough to sit down and nerd out with the founder & CEO of a company who’s betting on this exact strategy.

Bill Kerr runs Athyna - one of the leading platforms for hiring remote talent. Here’s a few reasons I’m buzzing about this write-up:

1. I’m a (small) investor in Athyna. Now, you might think this means “time to ignore everything that follows”. However, I’d say the opposite. Since my money is where my mouth is on this one, today’s piece brings a unique level of consideration (akin to a ‘personal investment memo’) that you don’t get to read (and I don’t get to share) every day.

2. Strategy Breakdowns is a happy customer. We made our first hire through Athyna, so we’ve seen first-hand how strong their offer is today. Now, we get to theory-craft their future together.

3. Access to behind-the-scenes info. I’ve been able to decorate this article with direct founder quotes, sneaky internal screenshots, and other treats you won’t find anywhere else.

With the (longest ever Strategy Breakdowns) intro out of the way - let’s get into today’s breakdown!

— Tom

Athyna’s “AI-for-talent” strategy

Chess Move

The what: A TLDR explanation of the strategy

Global talent is an unmistakeable mega-trend for internet businesses today. We won’t go into the history / macroeconomic forces / implications here (since that’s thoroughly well-documented elsewhere), but here’s the TLDR:

50% of all businesses were outsourcing some work, and 38% rely on talent platforms to build their global teams. Looking ahead, 48% of companies plan to increase their use of hiring platforms in the next two years (Source)

Why?

Pain points of traditional hiring:

• Talent: Limited access to higher-paying, flexible, global roles

• Employers: Small talent pools means lower quality role matches, longer hire times, and artificially inflated costs

Benefits of global hiring:

• Talent: Increased access to higher-paying global roles, with improved flexibility and mobility

• Employers: Larger talent pool, better matches, faster placements, for a price more reflective of an efficient global market

To indulge in a brief anecdote - one of the Jeff Bezos philosophies that’s given Amazon such enduring momentum is their ability to ‘focus on the constants’; the customer needs that never change.

For Athyna, those ‘constants’ are:

• Quality talent

• Accurate role fit

• Fast time-to-hire

• Low cost

_{Nabbed these screenshots snooping around the internal Athyna.ai strategy wiki. Don’t tell Bill.}

To supercharge each of these ‘constants’, Athyna has raised $2.5m To Build Athyna.ai: Incredible talent, matched with AI-precision, at lightning speed.

If you’re excited by this play like me and want to participate, click here for more details on investing in the community fundraising round. (This is not financial advice. Do your own research.)

Or, if you’re looking for your next global hire, click here to get started with Athyna.

Breakdown

The how: The strategic playbook boiled down to 3x key takeaways

1.  Incredible talent

The first exam question for any recruitment business is:

How do we access great talent?

Athyna isn’t new to the party - they’ve been in business for 5 years, and already have an expansive talent network with hundreds of thousands of applicants.

In fact, they claimed their wedge by focussing initially on providing US startups with technical talent that’s previously worked at top companies like Google, Amazon, Microsoft, Salesforce, and Uber.

For Athyna, today’s question becomes:

How do we expand our access to talent in the age of AI?

Here are 2 AI strategies they’re betting on to bolster both sides of the ‘Depth of Talent’ equation:

Strategy #1 - Ava: Athyna is uniquely positioned to build Ava, an AI-powered job search tool to help candidates land their dream gig. Optimise your LinkedIn profile, generate tailored resumes, and run their proprietary AI Matching Index across jobs you think you might be a fit for.

→ Size of talent pool: By creating massive value for job-seekers, Ava connects Athyna with a tech-forward, motivated, and AI-native segment of the talent market.

→ Usage of talent pool: Ava’s first-party product data gives Athyna even better visibility into key talent insights such as job-search status, work readiness, and personal preferences.

Strategy #2 - Job Board: Athyna is building a global jobs board for not only Athyna jobs, but all remote jobs.

→ Size of talent pool: The job board creates a new surface for inbound talent generation to Athyna. This expands the size of the pool that can be considered for Athyna jobs.

→ Usage of talent pool: Like Ava, the job board doubles as a data play. Measuring traffic, clicks, job page views, visit durations, bounce rates, applications started, applications submitted, and countless other data points enables better understanding, and therefore usage, of the available talent.

2. …matched with AI precision

The second exam question for any recruitment business is:

How do we match the right talent to the job?

When it comes down to it, talent-role-fit is a matter of matching variables with one another:

• Skills

• Timing

• Experience

• Motivations

• Compensation

Even for more nuanced aspects like ‘culture’, you are still ultimately looking for “does the candidate’s personality / values / quirks fit the employer’s?”

Historically, this has been one of gnarliest problems to solve in talent acquisition, since there’s such a large volume of variables that go into pairing the right match.

A perfect example of something that can be solved (or at least dramatically improved) algorithmically.

One of the things AI is already significantly better than humans at is ingesting extremely large volumes of data.

With Athyna investing into Ava, job boards, AI skills assessments, analytics engines, and other initiatives that expand the talent pool and the density of data points across that talent pool, this feels like a clear winning bet.

A human without an AI won’t be able to compete against a human with an AI once the game involves millions of data-points on millions of applicants.

3. …at lightning speed

Not only can AI ingest far more data than a human, it can also do so much faster.

Several orders of magnitude faster.

Bringing days of work down to seconds.

Imagine you’re recruiting for a role where cultural fit is incredibly important to the employer. How long would it take you to read 10,000 applicant cover letters and 100 employer strategy / culture / values documents?

When Strategy Breakdowns made our first hire through Athyna, one of the things that stood out was their velocity. Within ~6 days of publishing the role, the first interview took place (after Athyna pre-screened hundreds of candidates).

Fast turnaround times mean (1) less time without a key role filled, (2) faster time-to-value, and (3) improved access to the quality talent that is actively looking for jobs.

I recall chatting with Bill at the time, asking what he thought their 1-2 critical success factors had been to date.

To paraphrase his answer: “We just provide way better results, way faster.”

Not the flashiest website. Not the widest range of geographies. Not the highest production content marketing.

Athyna invested all its energy in finding the best candidate for the job, as fast as humanly possible.

And that was pre-AI revolution.

With all the systems, processes, talent networks, and data sets already in place as a byproduct of their existing strategy, Athyna are perfectly poised to capitalise on their speed advantage in the age of AI.

Rabbit Hole

The where: 3x high-signal resources to learn more