The enterprise data base of the longer term is a gathering centric data base. “It’s voice data,” says Sam Liang, founder and CEO of voice transcription firm Otter.ai. However to attain an efficient and natural repository of all enterprise exercise in real-time, all the things have to be recorded. Liang imagines a future wherein apps like Otter.ai shall be “all the time on” and all conferences shall be recorded and uploaded routinely. “You received’t even want to recollect to press a button,” he effuses.
For this state of affairs to evolve as Liang imagines, the present cultural shift in the direction of radical transparency might want to advance additional. A lot is generational. Youthful staff who dwell their lives on-line are digital natives and don’t have the privateness objections of older colleagues.
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Liang based Otter.ai in 2016 with fellow laptop science engineer Yun Fu, each of whom had an extended historical past of working with AI. On the time, Liang recounts how resistance amongst buyers to recording conferences was robust. “VCs informed me no person will use this [Otter.ai] as a result of no person needs to be recorded. Folks shall be scared. However VCs usually are not excellent at predicting the longer term and so they don’t perceive behavioural change,” says Liang who has since grown the corporate to $100m annual recurring income and over 25 million customers worldwide.
Whereas Otter.ai has change into a priceless subscription-based voice transcription device for customers throughout numerous professions, the corporate’s focus is firmly on capturing the enterprise market with its enhanced AI options. Enterprise clients already embody Walgreens, NBC Common, Grant Thornton and IBM. However Otter.ai launched a set of enterprise instruments on 7 October with a view to increasing its attain into the enterprise market. At a time when enterprise AI investments have gotten much less hyped and extra scrutinised, Liang says Otter.ai’s draw is effectivity that gives tangible return on funding (ROI).
In line with knowledge drawn from Otter.ai’s enterprise clients’ personal ROI calculations, the platform saves the equal workload of a single full-time worker for each 20 customers. An organization with a thousand customers, for instance, saves 50 full-time worker’s price of labor translating to over $6m in annual value financial savings (based mostly on $125K per full-time worker).
Behind the ROI knowledge, if Liang had been to get granular about time saving processes, he says it’s a lot greater than Otter.ai’s capability to generate assembly notes. Whereas staff can audit and search assembly notes within the evaluation part, they’ll skip conferences altogether. “You don’t have to take a seat via a two-hour assembly however nonetheless say knowledgeable by spending simply 10 minutes to get the data you want from a 90-minute assembly,” explains Liang.
Conferences are, by far, the costliest exercise in enterprises. And in line with ArchieApp’s October 2025 statistics, staff spend 11.3 hours per week in conferences, which equates to nearly a 3rd of the typical work week. Senior executives spend round 50% of their work week in conferences. Assembly time prices a median of $29k per worker per 12 months, not together with the additional hours spent on scheduling.
When pressed on how Otter.ai can compete with a few of its massive blue-chip opponents like Microsoft copilot or Zoom AI companion, Liang says its massive opponents are much less revolutionary. “They’re actually good at copying different firms, however they’re often late,” he says citing the instance of messaging platform Slack which Microsoft didn’t copy till Slack was a $10bn firm.
“So we do compete towards them ultimately, however we’re all the time forward of them when it comes to innovation. And the benefit we now have over Microsoft is our platform agnostic nature. Microsoft solely helps Microsoft. However we assist all of the assembly platforms, Zoom, Microsoft, Google.”
Transparency is vital for the environment friendly enterprise
However the true magic of an agentic AI pushed conferences platform has but to be realised, in line with Liang. The cross performance delivered by breaking down data silos inside an organisation will be finished most successfully via a conferences platform. That is the place enterprise leaders want some creativeness.
Spoken or voice data will very quickly surpass written documentation as essentially the most priceless enterprise knowledge as AI delivers on its promise to totally draft and ship accomplished written documentation.
“Historically, when individuals discuss data base, they solely take into consideration written paperwork. Nearly everybody has neglected voice data. Now we’re capturing voice, digitising and indexing all the things,” says Liang. Primarily, Liang and Otter’s future is a wholesale guess on an organization’s voice data base changing into the dominant knowledge data base of the longer term.
Voice knowledge gathered at conferences represents a real-time image of what’s occurring inside the organisation. “Within the trendy enterprise world, the market adjustments, merchandise adjustments, buyer adjustments, all the things adjustments so quick that conferences have essentially the most up-to-date data in comparison with written plans or documentation. Plans you wrote a month in the past could also be already out of date, or maybe 30% out of date, however the conferences often have the hottest data,” says Liang.
However it’s the cross performance of an agentic AI system that may extract essentially the most worth from a platform like Otter.ai. Totally different groups inside an enterprise – advertising, gross sales, product and buyer success groups – all have their very own conferences, however the data is often siloed and never shared shortly regardless of so many cross purposeful dependencies, with most counting on beforehand made a plans or schedules.
Otter.ai has a Slack-style workspace construction which helps organise conferences utilizing both public or non-public channels. “We encourage enterprises to make as many conferences as attainable clear, in order that their enterprise can function far more effectively.
The corporate practices what it preaches. All conferences at Otter.ai are shared publicly, apart from a number of HR conferences, or some extremely confidential conferences which stay in non-public channels. Nearly all buyer and gross sales conferences are shared transparently inside the corporate, so that every one departments get first-hand buyer data. For example, this informs the product group what clients want and what issues they’re having with present merchandise, in addition to what extra product options they want, all in real-time.
Transparency versus privateness – a zero sum recreation?
Liang is a passionate advocate of wholesale transparency inside the enterprise, believing the advantages outweigh privateness considerations. However the resistance he felt from buyers in his early fund-raising days stays, as privateness turns into a central concern within the march in the direction of world AI adoption.
In current months the corporate has change into a part of a wider dialog in regards to the growing use of AI transcription instruments inside the office. In August, the corporate was accused in a federal class-action lawsuit of deceptively and surreptitiously recording non-public conversations with out acquiring permission after which utilizing them to coach its AI fashions.
The lawsuit claimed that the corporate’s real-time transcriptions of Zoom, Google Meet and Microsoft Groups conferences, don’t require permission to file from attendees and that the corporate makes use of these conversations to coach its AI fashions.
Nonetheless, Otter says its privateness coverage discloses the transcription content material getting used for AI coaching. It says it gives an express opt-in possibility that permits Otter and third events to make use of the non-public conversations “for coaching and product enchancment functions.”
As for privateness inside the enterprise, Liang encourages the wholesale recording of all conferences with only some exceptions. Otter.ai gives the flexibility to create guidelines to maintain some conferences non-public. “You’ll be able to create guidelines, for instance, if this assembly entails this particular person it ought to all the time be saved non-public, or if this assembly has a sure key phrase, you may create sure tag within the assembly title or within the assembly description that gives the instruction to not share publicly,” explains Liang.
“We now have created a system that lets you create guidelines to manage the visibility of every assembly, and we’re engaged on guidelines that specify to not file sure conferences,” he provides.
Liang advises enterprise leaders to maintain an open thoughts and overcome privateness fears. He notes that almost all of current privateness legal guidelines had been created earlier than the appearance of the web. “I do suppose privateness legal guidelines must be enhanced to assist the brand new AI world,” he provides.
For enterprise leaders, Liang’s recommendation is to first recognise how AI is altering the world they function in. “So then the best way they function ought to change as nicely. Early adopters are transferring ahead with this expertise. There’s nearly no selection if you wish to make your enterprise extra productive.”
Liang’s strategy of main by instance has seen the corporate constructing particular workflows for these enterprise leaders. He says some 95% of his personal conferences are recorded and shared with all attendees and 50% of his conferences are clear to the broader enterprise. “I, myself, as a founder and CEO of Otter must handle so many initiatives, so many alternative departments. I truly depend on Otter to realize insights about how issues are working inside the firm,” he explains.
Liang’s hope is leaders will see for themselves how a device like Otter will assist them handle their firm higher, and can then recognise the worth and change into satisfied of the broader advantages for his or her firm.
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