Podcast Summary: The Agile Brand with Greg Kihlström

Episode #807: AI21 Labs CMO Sharon Argov on Navigating Promise vs. Reality with AI Adoption

Date: Feb 4, 2026
Host: Greg Kihlström
Guest: Sharon Argov, CMO at AI21 Labs

Episode Overview

This episode explores the tension between the extraordinary promise of artificial intelligence (AI), specifically generative AI, and the messier reality enterprises face during its adoption. Greg Kihlström and Sharon Argov discuss the practical and strategic challenges marketing/technology leaders encounter when bridging the gap between the technical depth of AI products and the compelling business narratives needed to drive adoption. Core topics include AI’s reliability, brand impact, risk management, trust, and the evolving skillsets leaders need.

Key Discussion Points & Insights

1. Bridging Perception vs. Reality in AI Adoption

• Sharon explains the unique barriers enterprises face between “the perception of AI and actual adoption, especially in the enterprise.” (01:49)
• AI21 Labs focuses on translating deeply technical products into accessible business discussions, making clear distinctions between what AI can do and its current limitations.

2. Turning Limitations into Strengths

• Sharon emphasizes acknowledging AI’s imperfections:

  "AI makes mistakes, it will continue to make mistakes. We talk about it very openly and we’re trying to estimate the cost of the mistake." (04:50)

• Rather than hiding limitations, AI21 Labs discusses the cost, impact, and risk of AI errors with customers to build trust, making clear distinctions for both technical and business stakeholders.

3. Mindset Shift: From Certainty to Confidence

• Unlike traditional SaaS which offers certainty, AI solutions provide confidence in managing uncertainty:

  "In SaaS you often sell some level of certainty, right? If you work with Salesforce, you will gain better outcome... With AI it’s a little bit different. What we’re selling is confidence and the ability to control under certain level of uncertainty." (06:38)

• The sales narrative shifts from deterministic guarantees to collaborative progress— “I can only promise you what we will do together with this technology versus those very shiny taglines on a SaaS production.” (07:32)

4. Brand Identity in the Era of Generative AI

• Branding remains people-centered, not technology-centered:

  "Branding is not about technology. Branding is about people, emotion, perception, dreams, feelings… we haven’t changed a lot in the last hundreds of years." (09:14)

• AI21 Labs’ “Build Boring Agents” campaign, designed to stress reliability over 'flashiness,' purposefully differentiated them from competitors by prioritizing predictability for enterprise contexts:

  "The purpose was to create awareness… we turned the most boring tasks into boring agents… the type of technologies that you can really rely on." (10:18)

5. Education as Differentiation

• Sharon highlights the need for market education due to confusion around terms like "agent":

  “Everybody talks about agent, but everyone refers to completely different things… because we have deep tech capabilities, we use it to teach and give full understanding.” (13:33)

• Their marketing team creates technical content (“labs in the front”), publishing detailed articles from their engineers as an outreach and trust-building tool.

6. Measuring AI Success: From FOMO to ROI

• AI investments are still early, but three KPI domains stand out:
  1. Scale & Growth: How AI enables faster, broader, or more efficient operations.
  2. Decision-Making: How AI insights support better, faster, or more accurate decisions.
  3. Risk Avoidance: How AI helps identify, mitigate, or avoid risks.

  “Those will be the three areas that we believe that AI will create the main ROI and the main impact that will be measurable in the next few years.” (16:28)

7. Future-Proofing: Agility and Curiosity Needed

• Sharon’s advice to marketing leaders:

  “It’s agility. It’s being flexible, agile. You need to have an agile attitude… It’s really the right answer for every department and every role.” (17:43)

8. Trust & Responsibility as Friction Points

• As AI matures, trust is the main frontier:

  “There’s a lot of questions related to trust. Who is responsible for a mistake that the AI is doing?... The level of trust and the ability to decide on the responsibility of the AI, those will be the things that we will need to understand in the next future.” (19:10)

9. Predictions for the Next Year

• Sharon expects continued slow enterprise adoption:

  "I think we're still going to speak about the low adoption at the enterprise. It's going to take time and to be honest, I think we will still be surprised that it does take time." (20:26)

Notable Quotes & Memorable Moments

• On Enterprise AI Mindset:
  "With AI it's a little bit different. What we're selling is confidence and the ability to control under certain level of uncertainty." – Sharon Argov (06:44)

• On Branding AI:
  "We turned the most boring tasks into boring agents… Dull in chat, never invent facts. The type of technologies you can really rely on." – Sharon Argov (10:18)

• On Trust and Responsibility:
  "Who is responsible for a mistake that the AI is doing? How do you enforce policy of organization on AI?... Would you trust them to read a contract? Will you trust them to invest for you in the stock exchange?" – Sharon Argov (19:17)

• On Staying Agile:
  "To stay agile? I constantly question my assumption. I try to remind myself that I don't know everything... keep an open and a growth mindset." – Sharon Argov (20:44)

Timestamps for Key Segments

• Sharon’s Role & AI21 Mission: 01:49–03:01
• Navigating AI’s Limitations & Narrative: 03:01–06:38
• Mindset Shift in AI (Certainty to Confidence): 06:38–07:43
• Branding in the Age of AI – ‘Build Boring Agents’ Campaign: 09:14–11:36
• Market Education & ‘Labs in the Front’ Program: 12:47–14:23
• Measuring Success & KPIs: 14:23–17:18
• Skills for the Future – Agility: 17:18–18:44
• Trust and Responsibility as the Next Friction Point: 19:10–20:12
• Predictions for 2027: 20:26
• Staying Agile as a Leader: 20:44

Takeaways for Listeners

• AI adoption is about managing uncertainty and building organizational confidence, not guaranteeing perfection.
• Successful AI brands focus on reliability and trust—sometimes even 'boring' beats 'exciting' for enterprise buyers.
• Education is both a differentiator and a necessity when selling technical products.
• Measurement must go beyond hype and FOMO, focusing on scale, informed decisions, and risk mitigation.
• Agility, curiosity, and a strong learning mindset are the most critical skills for both marketing leaders and teams.
• Trust, responsibility, and a cautious approach to errors will be even more central as AI becomes more integrated.
• Enterprise adoption of generative and agentic AI will remain a slow-burn process—don’t expect hockey-stick growth just yet.