From: redpointai
The integration of artificial intelligence (AI) into human communication is rapidly evolving, promising to fundamentally transform how people interact both personally and professionally. Rahul Roy-Chaudhury, CEO of Grammarly, an AI assistant app for writing, shares insights into this future, envisioning a world where AI streamlines communication, allowing for deeper human connection and greater efficiency [00:00:08].
Envisioning Communication in 10 Years
In the next decade, AI is expected to take over much of the “drudgery” of day-to-day work, enabling individuals to focus on creativity, synthesizing ideas, and connecting more meaningfully with others [00:01:45]. The hope is to send and read fewer emails and documents, as the average person currently switches contexts 1,200 times in an average workday [00:02:00], [00:02:27]. The goal is not to create more content or volume, but to make communication “better, more memorable, more evocative, more on point, more kind of precise” [00:02:11].
This shift aims for a future where each conversation becomes “measurably more valuable” [00:02:47]. The ideal outcome involves fewer, but more significant, emails and texts that facilitate connection or lead to important decisions [00:02:55]. However, there is an alternative, less desirable future where the cost of content production becomes zero, leading to an overwhelming amount of AI-generated content, which would then require AI to consume [00:03:21]. Roy-Chaudhury emphasizes that writing and communicating are integral to being human and should not be fully outsourced to AI [00:03:40].
Evolution of AI Assistance in Communication
Grammarly, having been founded in 2009, has continuously adapted its technology from rule-based systems to deep learning models, and now to large language models (LLMs) and generative AI (gen AI) [00:04:13]. The approach is to identify user problems and then apply the best available technology to solve them [00:04:32].
Historically, Grammarly focused on the “revision” phase of communication [00:05:23], helping with correctness, tone, organizational style guides, and brevity [00:05:37].
The advent of LLMs enables significant advancements:
- Tying Communication to Business Outcomes [00:06:04]: AI suggestions will become more strategically aligned with desired outcomes. For instance, Grammarly might suggest adding “free food” to an event email to drum up enthusiasm or a clear call to action for an email to a board [00:06:25]. Mechanics like correctness and tone will often be auto-applied [00:07:08].
- Full Communication Lifecycle Support [00:07:22]: AI assistance will expand beyond revision to include ideation, composition, and comprehension [00:07:27]. For example, users could ask Grammarly to summarize long email threads or identify action items within them [00:07:40]. This aligns with the broader future of email and AI integration.
Challenges and Quality Control
While LLMs are powerful, it’s still early days [00:08:24]. Given the high stakes of written communication, Grammarly heavily fine-tunes models for specific use cases, conducting extensive quality and safety evaluations to prevent false positives, sensitive text issues, or other safety concerns [00:08:50]. This involves:
- User Feedback Loop: Tracking how users accept or reject suggestions and engage with features provides continuous quality input [00:10:02].
- Human Evals: Human experts rate LLM outputs against curated outputs to determine preference and objective quality [00:10:28].
- Experiments: Features are released to a small percentage of users to gauge real-world engagement and identify issues before broad rollout [00:10:52].
- Contextual Sensitivity: Learning from user feedback, such as a police department’s request to disable “sound more positive” suggestions when typing crime reports, helps identify inappropriate contexts for AI suggestions [00:11:42].
Impact on Communication Workflows
The future of communication with AI will involve more complex, multi-step workflows. As models become capable of multi-step reasoning, they can enable AI agents to orchestrate complex communication flows [00:21:24]. This means AI could help in crafting important documents like a board email by:
- Gathering Context: Pulling relevant information from various internal sources (e.g., marketing, engineering, cost structures, PR plans) [00:20:56].
- Hypothesizing Steps: Suggesting the best set of steps to compose the communication, understanding audience needs (e.g., board emails need to be brief and succinct) [00:21:11].
- Reducing Drudgery: Minimizing the “cutting and pasting context” that makes up a significant part of current work, such as summarizing detailed emails for different audiences [00:21:43].
This advancement aims to make communication “magical, easy, super smooth,” allowing users to achieve a “Flow State” [00:22:06].
Personalization and Enterprise Adoption
AI in communication is moving towards deeper personalization. For individuals, AI will help users sound “more like you,” capturing their unique voice, with the goal of automating most of this process over time [00:26:40].
For organizations, AI tools like Grammarly can enforce style guides, brand tones, and corporate values across all internal and external communication [00:26:54]. This ensures consistency and compliance, automating what might otherwise be “25,000 rules” in a large document [00:28:01]. This is achieved through a combination of fine-tuning models on specific use cases and ingesting organization-specific knowledge into the AI system [00:27:37].
AI is poised to transform the workplace, though this will be a multi-year journey, similar to the shift from on-premise to cloud computing [00:36:05]. Enterprises seek AI vendors they can trust for this long-term transformation [00:36:50]. While there is much experimentation, measurable productivity gains from AI are still somewhat elusive, beyond specific use cases like software engineering and code generation [00:37:21]. However, tools like Grammarly demonstrate clear value, with the average user saving 19 days per year on communication-related tasks [00:38:03].
The Role of AI in Education
AI is emerging as a powerful, yet potentially misused, tool in education [00:39:51]. Similar to how calculators or looking up code snippets online were once considered cheating, AI is now being integrated into pedagogical methods [00:40:07]. Educational institutions are moving past banning AI to focusing on how to responsibly equip graduates with the critical skills needed for an AI-infused workforce [00:40:51]. This directly impacts the future of AI in education.
Grammarly has developed features like “cite your use of AI” and “Authorship” [00:41:16], [00:42:27]. Authorship provides provenance for every part of a document, indicating whether it was written manually, cut and pasted, or AI-generated [00:42:38]. This transparency allows educators and students to set their own acceptable boundaries for AI use, ensuring that the technology helps deepen understanding rather than enable disengagement [00:42:52].
Ultimately, AI should serve as a tool to give humans “superpowers” and augment their capabilities, not displace them [00:44:24]. In education, this means using AI to engage better with material, receive real-time feedback, and act as a leveler, particularly for students globally who lack access to traditional educational resources [00:44:40].
Broader Implications and AI’s Impact
Beyond direct communication tools, AI will significantly change how people interact with information and consume content, as seen in web browsers [00:45:50]. Future browsers will likely embed AI to synthesize information, remember past interactions, and surface relevant data at the right moments, potentially even solving the “too many tabs” problem [00:46:04].
Furthermore, AI is viewed as an “underhyped” tool for upskilling and upleveling individuals globally, acting as a “democratizer of skills” and a “force multiplier” for those struggling or lacking specific abilities in the workforce [00:46:52]. Initial studies suggest AI is most impactful for individuals in the lower half of ability in certain tasks, making it a compelling tool for widespread improvement [00:47:29].
The distinction between consumer and enterprise AI use is becoming increasingly artificial, as many users buy AI tools for personal use but apply them in their professional lives [00:49:15]. This seamless customer journey, from free versions to premium and team licenses, highlights the pervasive nature of AI’s integration into daily communication [00:49:39].