# Yong S. Kim

Yong S. Kim writes about improving sales systems and putting AI to practical use in healthcare SaaS teams, with a focus on process, data, coaching, and repeatable workflows.

- Profile: https://b2binfluencer.marketing/creators/yong-s-kim/
- LinkedIn: https://www.linkedin.com/in/yongskim
- LinkedIn followers: 6,937
- Median of last 9 posts: 6 reactions, 0 comments (checked 2026-11-02)
- Topics: artificial-intelligence, sales, healthcare, sales-coaching
- Based on 11 dated posts, latest 2026-10-02

## Summary

Most useful for assessing sales systems and AI readiness before choosing tools.

- Best for: Healthcare SaaS teams with 30 to 60 sales people considering a diagnostic or advisory engagement.
- Not for: AI sales-tool vendors seeking sponsored product launches to general B2B SaaS audiences.
- Check first: Confirm commercial terms, audience demographics, and engagement data before treating this as a paid sponsorship.

### Takeaways

- AI multiplies a sales process instead of repairing it.
- Fix the system under the funnel before buying more leads, tools, or headcount.
- AI adoption is a workflow problem, not a tool problem.

## Main ideas

- **AI multiplies a sales process instead of repairing it**: Kim's central argument is that AI is a multiplier, not a fix: strong process gets faster, broken process breaks at scale. The foundations named stay consistent across posts — ideal customer profile, messaging, CRM hygiene, a playbook, and a coaching structure — and most of the writing is spent on what goes wrong when tools arrive before those exist. The test Kim offers a buyer is blunt: would this strategy work without the technology? If not, the tool will not save it.
- **Fix the system under the funnel before buying more leads, tools, or headcount**: Kim's recurring diagnosis of stalled revenue growth is that leadership treats the funnel as the problem when the system feeding it is. The named causes are organisational rather than technological — inconsistent messaging, no qualification framework, no coaching cadence — and the consequence is reps improvising their way through deals that should have been disqualified early. The priority Kim sets is engineering that system first, which is why the same argument reappears as the reason a new tool will not help.
- **AI adoption is a workflow problem, not a tool problem**: Kim treats uneven AI use as the predictable result of leaving adoption to individual habit. The proposed fix is deliberately unglamorous: every AI use case gets a trigger, a defined output, and an owner, with the manager checking the output. Kim's framing of the alternative is that telling a team to use AI more is a wish rather than an instruction, because nothing about the work changes.
- **Define what a good lead is before switching on AI lead scoring**: Kim frames scoring as a sequencing problem rather than a tool problem. A scoring model finds patterns in historical wins, so if those wins were the wrong customers, the model learns the wrong lesson and scales it. Kim's stated priority is completing the ideal-customer work first and treating the model's ranked output as a test of that definition rather than as the definition itself.
- **The call library is an unmined asset, and a manager has to act on the signal**: Coaching is the other half of Kim's argument. Conversation intelligence platforms already hold the material a playbook needs, in Kim's account, and most sales organisations leave it unmined. The constraint Kim attaches is that surfacing the data is not the same as using it: AI produces the signal, and a manager still has to do something with it, which is why coaching capability is listed alongside process as something a new tool cannot substitute for.
- **Add capacity inside the team before outsourcing the pipeline, with one stated limit**: Kim's case against outsourcing is about scale rather than hourly rate: a single offshore hire is manageable, but a team becomes a second management layer, with someone owning quality control, someone covering the time-zone gap, and someone rewriting instructions whenever the process changes. Turnover then takes the institutional knowledge with the person who held it. The alternative Kim proposes is AI built into the workflows the existing team already runs, on the reasoning that it needs no handoff, ramp-up, or dedicated manager. Kim does not rule outsourcing out entirely — the position is scoped to customer-facing pipeline work rather than stated as a blanket rejection.
- **Give buyers a diagnostic or a short question list before any sales conversation**: Rather than pitching a service, Kim routes readers to self-assessment and short checklists. One recurring format is the pre-purchase question list aimed at people about to take a vendor call; another is a readiness assessment that reports where AI could genuinely help, where the team is not set up to get value yet, and what to prioritise instead of chasing every new tool. Kim states explicitly that the assessment carries no cost and no sales pitch.

## Work to read

- [Sales Isn't a Funnel. It's a System.](https://www.linkedin.com/posts/yongskim_sales-isnt-a-funnel-its-a-system-more-activity-7481300215124099072-9Qia)
- [Most sales teams don't have an AI problem](https://www.linkedin.com/posts/yongskim_most-sales-teams-dont-have-an-ai-problem-activity-7520816745054572544-X5MX)
- [Your CRM is the foundation AI can't save](https://www.linkedin.com/posts/yongskim_your-crm-is-the-foundation-ai-cant-save-activity-7504516669080530944-0z2-)
- [Individual habits don't scale. Workflows do.](https://www.linkedin.com/posts/yongskim_every-rep-on-the-team-had-access-to-ai-almost-activity-7521179970124304384-HGGY)
- [AI Can Score Your Leads](https://www.linkedin.com/posts/yongskim_ai-can-score-your-leads-but-only-if-youve-activity-7509575083540230145-YKdK)
- [The AI Sales Tools](https://www.linkedin.com/posts/yongskim_the-ai-sales-tools-healthcare-saas-companies-activity-7499443239955980288-a46j)
- [AI doesn't replace your Sales Manager](https://www.linkedin.com/posts/yongskim_how-to-use-ai-to-coach-your-sales-team-without-activity-7514663556718592001-HlvD)
- [Find Out Where AI Will (and Won't) Help Your Sales Team](https://www.linkedin.com/posts/yongskim_assessment-ai-readiness-kore-strategies-activity-7484206850331131904-8FRF)
- [When a team runs out of capacity, the reflex is to outsource](https://www.linkedin.com/posts/yongskim_when-a-team-runs-out-of-capacity-the-reflex-activity-7521541887208587264-IF-x)

## Partnerships

The reviewed material contains no documented sponsorship, advertising, or paid-partnership formats for Yong S. Kim. The supplied LinkedIn posts are about sales systems, AI readiness, CRM data, coaching, and healthcare SaaS; none describes sponsored placements, rates, deliverables, or a media kit. The one outward-facing offer found is a free AI Readiness Assessment for sales teams, described in a July 2026 post as a 10-minute diagnostic with no cost and no sales pitch attached. That is a self-serve lead tool, not a purchasable sponsorship format, so it is not listed as one here. This is an absence of documented sponsorship formats in the reviewed material, not a claim that Yong S. Kim never accepts sponsorships. Because no official partnership or sponsorship inquiry route appears in the evidence, no inquiry link is provided; a general LinkedIn profile is not a partnership contact and has not been substituted for one. A brand planning an engagement should treat this section as an open research gap to confirm directly before budgeting.

## Alternatives

- Hudhayfah M.: Choose Hudhayfah M. when the healthcare SaaS company's real problem is that its pipeline depends on referrals and has no repeatable outbound rhythm. Both supplied posts make that case directly: referrals are not a growth strategy because you cannot decide when someone recommends you, control how many introductions arrive next month, or forecast revenue around them. The proposed alternative is a channel the company controls, with LinkedIn outbound as the named example, plus a weekly system that tracks who is being contacted, how many conversations start, how many meetings get booked, and what needs improving. That makes this the better pick for an early-stage or founder-led team where the diagnostic should end in a first working outbound cadence rather than an AI roadmap.
- Greg Walder: Choose Greg Walder when the buyer wants to see what AI-native go-to-market work actually looks like inside a company, not a method for deciding whether to start. The two supplied posts describe concrete builds: an account handoff that pulls context from call recordings, email, CRM data, enrichment systems, and internal notes to assemble a structured customer handoff, recommend which CSM should support the account, route the result through account-executive approval, and generate branded kickoff material; and a deal-qualification workflow that scores a deal against a rubric, compares it to past deals, flags missing information, and explains the reasoning behind its score instead of just returning a number. That is the stronger choice when the engagement is an implementation showcase for a team that has already accepted the AI direction and wants a build to aim at.
- Dev Basu: Choose Dev Basu when the brief sits on the marketing side of the same problem: demand that is not converting, misalignment between marketing and sales, or deals stalling on multi-stakeholder content. The 100-day plan for a new marketing leader walks through auditing closed-won deals, mapping channels against pipeline produced, checking the real MQL-to-SQL rate, auditing attribution, and interviewing recent losses and losses, then aligning the ideal customer profile with sales, agreeing on what a good lead looks like, and putting bottom-of-funnel content and landing pages live. A second post breaks a B2B deal into its six stakeholder questions, from champion and executive through finance, IT and security, operations, and legal, and argues that most teams build content for only one of them. For a healthcare SaaS company whose deals need several approvers, that mapping is closer to the daily problem than a general AI-readiness pitch.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/