Bear in mind HAL 9000 from “2001: A House Odyssey”? The eerily calm, near-sentient robotic? It was a reliable coworker for the people onboard. Effectively, at the least earlier than it turned rogue (extra on that later).
HAL represents one among science fiction’s most iconic visions of synthetic intelligence (AI) with autonomy — an AI system that would observe, motive, and act independently to attain its goals.
That is a glimpse of agentic AI in motion. Because the identify already provides away, agentic AI has company. Working on massive language fashions (LLM), it really works with out human prompts. It not solely creates and plans duties however executes them by itself. And all of this isn’t simply sci-fi anymore; it is the following huge factor for tech giants. Salesforce deems it “era-worthy,” and McKinsey touts it because the “subsequent frontier of generative AI.”
“The AI brokers market is anticipated to develop at 44.8% CAGR between 2024 and 2030, pushed by technological advances in pure language processing (NLP).”
One notable growth within the agentic AI breakthrough is that it warps how we’ve seen AI thus far: hand-held instruments that assist us. As an alternative, AI brokers are proactive digital coworkers which may simply be reshaping how groups are structured, how employees work together, how duties have to be divided, and extra.
This shift additionally raises an unsettling, maybe sinister, query: are so many human employees wanted within the first place?
Backed by information from 3,621 evaluations, this text explores how AI brokers are getting used within the office at this time and what which means for the way forward for work. By inspecting their commonest purposes, utilization patterns, and different insights, we will perceive not simply the place AI is making an affect however the way it’s reshaping group buildings, decision-making, and the division of labor between people and digital coworkers.
Let’s get into it.
What’s agentic AI and the way does it work?
Let’s start with what agentic AI is.
Agentic AI was first developed within the 2000s when machine studying (ML) fashions allowed brokers to study and enhance utilizing massive databases. In the present day, the agentic AI panorama is predicated on superior autonomy, enmeshed with an moral and accountable AI-controlled atmosphere.
Though we at G2 use the time period AI brokers to consult with “software program methods that may motive, act, and automate autonomously,” that is certainly not the one present or accepted definition, explains Matthew Miller, analysis principal at G2.
Largely, AI brokers are autonomous digital employees that use instruments to perform objectives. These brokers have the power to recollect throughout duties and altering states, in line with BCG.
However what does this seem like in observe? To know their affect, let’s study an business that’s already seeing AI-driven transformation: content material advertising and marketing.
The human advertising and marketing supervisor assigns the AI agent a imprecise situation: create a weblog put up on the most recent digital advertising and marketing traits. The agent then researches for it, submits a graphic design request, drafts a weblog, and phases it on a content material administration system. The supervisor lastly steps in to evaluation it earlier than the agent schedules it for publication. It additionally creates and schedules social media posts for promotions.
Whereas this instance demonstrates the autonomous capabilities of agentic AI, many individuals may surprise how these methods differ from the AI assistants they’re already aware of. In any case, hasn’t AI been serving to with content material creation for a while now? This raises an necessary query concerning the distinction between really agentic methods and their extra restricted predecessors.
Is agentic AI totally different from chatbots?
Tim Sanders, vp of analysis insights at G2, believes there’s a gradient to agentic AI. “I prefer to name it the Waze-to-Waymo continuum.”
He provides that the entry level to this spectrum is co-pilots or chatbots. And that the highest of this continuum is occupied by “system of brokers.” “Brokers right here, on the highest stage, span throughout methods and collaborate and ship in your intent and never simply your acknowledged want,” clarifies Tim
Supply: LinkedIn put up by Tim Sanders
He additionally argues that agentic AI is an enormous deal because it solves the supply downside customers and organizations may face with chatbots and automation, “The supply downside is that particular person productiveness features don’t essentially translate into organizational elevated velocity of outcomes.”
For instance, human content material writers may save 30% of their time utilizing writing assistants, however they may squander it on taking a nap, scrolling by way of social media, or attending extra conferences.
As customers of AI brokers — the persona remains to be evolving as sellers experiment with purposes — have begun integrating them into their workflows, sure patterns have emerged. These point out how customers want to make use of these brokers and their likes and dislikes, which in flip exhibits the affect AI brokers have had on work. Let’s focus on them based mostly on consumer evaluations.
Agentic AI in motion: who’s utilizing it, what they suppose, and the affect
To know using AI brokers, we analyzed 3,621 evaluations made by verified customers worldwide on G2. We discovered that agentic AI is mostly utilized in pc software program, IT, and providers industries, adopted by monetary providers.
These brokers are additionally broadly accessible and helpful for companies of all sizes, not simply massive enterprises.
“AI brokers aren’t only for the large established corporations. In keeping with G2 evaluations from the previous 12 months for AI brokers, over half (55%) of evaluations are from small companies.”
Matthew Miller
Analysis principal at G2
Moreover, the truth that “AI chatbots”, “AI brokers”, and “chatbots” are the most well-liked AI classes by way of site visitors on G2 testifies to the rising curiosity in agentic AI amongst customers.
Sentiment evaluation of the AI brokers class
After analyzing 500 consumer evaluations between September 2024 and February 2025, we discover that 87% are optimistic, whereas simply 4.6% are adverse. This suggests important satisfaction ranges and the ensuing adoption of AI brokers, that are nonetheless of their early kinds.
Let’s perceive the consumer sentiment extra deeply and its implications for each patrons and sellers of AI brokers.
What customers like essentially the most
- Ease of use: Customers admire that the software program on this class is intuitive and simple to navigate.
- AI capabilities: AI capabilities are a robust level, with customers mentioning their effectiveness.
- Buyer help: Many evaluations spotlight glorious customer support and help.
- Effectivity: Customers be aware that the software program helps automate duties and enhance workflows.
- Integration: Seamless integration with current instruments and platforms is a plus.
- Reducing time to ROI: The time to ROI has decreased from 16.9 months in 2023 to 9.5 months in 2024.
G2 Take
The emphasis on ease of use is a driving consider agentic AI’s adoption. The democratization will speed up its use throughout sectors and capabilities and attain non-technical customers.
Customers additionally worth buyer help, impressing the human-AI collaboration in onboarding and launching agentic AI options.
Stressing the lowering time to ROI, Yukta Rustagi, a market analysis analyst at G2, provides, “This additionally implies that organizations leveraging AI are gaining a aggressive edge by way of effectivity and innovation. It reinforces the assumption that AI brokers at the moment are a extra rapid and impactful funding for companies.”
ROI for AI Brokers class (Jan 2023 – Dec 2024)
Supply: G2 Market Analysis
Challenges and what they imply
Customers have highlighted function limitations in AI brokers. However this doesn’t essentially point out performance gaps. As an alternative, the expertise’s infancy involves the fore, revealing that we’re nonetheless creating shared concepts of what agentic methods ought to accomplish throughout domains.
Options for particular person customers may be constructed on common options that serve a number of wants. Nonetheless, enterprises want specialised options that resolve issues at scale. Thus, AI brokers for bigger corporations should goal particular use instances corresponding to coding, stock administration, and lead qualification.
AI brokers current a customization problem, in contrast to that seen with earlier AI makes use of. They’re rising as adaptive methods that personalize by way of interplay somewhat than configuration. Thus, corporations could not must customise AI brokers, that are thought of digital coworkers, any greater than they customise human colleagues.
Some customers battle with coaching AI fashions, which could hobble adoption and delay the time to ROI. AI brokers, as autonomous options, should want minimal coaching. They need to adapt to customers, not vice versa.
The educational curve will stay steep if customers proceed to suppose within the command-execution paradigm with AI brokers, which function by way of purpose delegation and autonomous planning. Each sellers and patrons should reimagine onboarding as a collaborative alignment between people and brokers.
Value issues amongst some customers point out low market maturity as companies battle to quantify agentic AI worth with out standardized metrics. Sellers have but to generate sufficient case research and predictable use instances to construct a stronger enterprise case for AI brokers.
Whereas AI brokers are getting used throughout industries, our evaluation of G2 evaluations reveals that buyer expertise is the world the place their affect is most pronounced. Almost half of the consumer evaluations point out CX-related enhancements, making it a pure focus for understanding the real-world advantages of agentic AI.
Buyer expertise: commonest affect space
Whereas analyzing evaluations for AI brokers, we discovered that 217 of them, or 43%, point out buyer expertise, making it arguably the most typical space of affect for corporations at this time.
Echoing the sentiment, Tim believes brokers are essentially the most employable in two use instances thus far: buyer help and gross sales growth.
“Buyer help groups at present face excessive backlogs, which agentic methods can shortly cut back. Gross sales growth leaders see little draw back to agentic SDRs, given their hard-to-fulfill quotas of lead era, booked conferences, and addition to the pipeline,” he explains.
“Within the subsequent 10 years, AI in CX will cut back the associated fee to serve by an order of magnitude, enabling manufacturers to develop touchpoints with prospects in a method that has by no means been attainable.”
Jason Maynard
Chief expertise officer of AMER and APAC at Zendesk
Matthew has discovered that agentic AI has had the largest affect on the shopper journey across the consideration section. “Though the readiness of patrons to depend on brokers is growing, buying nonetheless stays a ache level,” he claims.
Presently, 30% of customers would work with an AI agent for quicker service. “We predict that it will improve because the methods grow to be extra dependable and as customers and companies develop extra belief towards the methods,” he says.
Most optimistic evaluations on G2 spotlight AI’s effectivity in buyer help and automation. Whereas adverse mentions (4.6%) embrace issues about AI errors, gradual help response, and lack of customization.
To help our findings on AI brokers use instances, we requested two customers how their expertise with AI brokers had been in enhancing buyer expertise, a preferred use case:
G2 Icons Communicate
G2 Icons are our most prolific contributors and energy customers of the G2 platform.
Person 1: Peter Gill, freight dealer
How do you employ AI brokers to boost buyer expertise?
We should perceive buyer necessities relating to pickup factors, supply factors, and commodity sorts to supply them with essentially the most aggressive charges and high-quality providers.
Earlier, we used to do that manually. Now, utilizing AI-driven chatbots and digital assistants, we will provide instantaneous responses to buyer inquiries, lowering resistance within the gross sales funnel. Moreover, AI helps us study buyer habits patterns, enabling us to grasp them higher in order that we will get repeat enterprise from them.
Results of agentic AI interventions:
- Buyer satisfaction scores up by 23%
- Uptick in ticket decision charge by 19%
- Lowered handbook work for groups by automating 33% of repetitive inquiries
Person 2: Luca Piccinotti, development marketer
How do you employ AI brokers to boost buyer expertise?
We use AI brokers to investigate market traits, section goal audiences, and forecast buyer habits, which in flip helps the event of exact messaging and tailor-made campaigns.
Results of Agentic AI interventions:
- Lowered ticket decision time
- Improved buyer suggestions
At first look, AI’s most rapid affect appears to be on buyer expertise — dealing with help queries, automating duties, and enhancing engagement. However what occurs when these identical AI capabilities are turned inward?
Simply as AI is reworking totally different industries, it’s additionally redefining how work will get performed, how groups collaborate, and what it means to be productive. As AI brokers transfer past buyer help and into core enterprise operations, their position within the office is turning into inconceivable to disregard.
Reimagining work: specialists weigh in
Agentic AI isn’t nearly mere automation however cognitive reallocation. It’s creating a brand new method to have a look at the division of labor the place people are elevated to higher-order considering roles.
To know this real-world affect, we flip to business specialists who’ve noticed AI brokers in motion, providing priceless insights into how companies are integrating them, the place human oversight remains to be essential, and what expertise can be wanted on this AI-driven future.
Right here’s what they must say:
AI brokers are the always-on teammates
Some peddlers of AI brokers are branding them as digital workers, others as teammates, and others nonetheless as instruments that stand behind customers versus between them, says Matthew.
To this, Tim provides, “They require much less human-in-the-loop efforts than LLM chatbots. We should always consider these brokers as group members that by no means take day without work, get distracted, or develop unhealthy attitudes.”
Mark Purdy, director of Beacon Thought Management, says AI brokers additionally carry out a wide range of specialised capabilities. For instance, brokers can collect info from a number of inner databases and exterior information sources, assessing and synthesizing the insights for enterprise analysts, attorneys, scientists, or different information employees.
AI brokers can act as casual sounding boards
AI brokers can perceive totally different enterprise issues and contexts, triggering actions and workflows that cut back the pressure on human employees,” factors out Mark. For instance, AI brokers can assess e-mail site visitors from prospects or purchasers, robotically responding to queries or complaints. They’ll monitor and comply with up on gross sales leads.
“AI brokers will help human managers and leaders make higher selections by operating totally different situations or simulations to indicate the outcomes of other programs of motion.”
Mark Purdy
Director of Beacon Thought Management
On this sense, AI brokers can function casual sounding boards for various decision-makers, whether or not on the supervisor or board stage.
Nonetheless, Mark additionally emphasizes that whereas AI brokers can act autonomously, there practically at all times must be some human-in-the-loop component to keep away from errors or unethical selections.
Human-(nonetheless)-in-the-loop
When requested how organizations should divide duties between brokers and people, Mark says the diploma of human involvement will rely on many components. These embrace the choice’s significance, the diploma of belief within the AI agent’s suggestions, the results of a mistake, and the human employee’s expertise and judgment.
“For instance, there’ll possible have to be a excessive diploma of human supervision in areas corresponding to healthcare or protection the place the results of errors by AI brokers may very well be very important, and doubtless much less want in areas corresponding to customer support or back-office processing,” says Mark.
Echoing the sentiment, Sreelesh Pillai, co-CEO at Zepic, says that the corporate’s AI brokers function independently, mimicking and amplifying human functionality whereas permitting companies to configure human involvement the place needed.
Overworked? AI may simply be the productiveness enhance you want
Leandro Perez, CMO for Australia and New Zealand at Salesforce, factors to a productiveness problem going through people. “As an example, for Australia, the productiveness development has fallen to thirtieth out of 35 comparable nations,” he says.
“Overworked workers want instruments that assist them work extra effectively.” And that is the place instruments like Agentforce, Salesforce’s agentic AI resolution, come into the image.
Leandro cites the instance of Fisher & Paykel, one among Salesforce’s prospects, which has saved over 3,300 hours month-to-month by reimagining their processes by way of AI brokers and automation.
“Agentic AI is not nearly effectivity; it’s about unlocking potential with limitless digital labor…you may count on to see each worker main or working alongside groups made up of AI brokers and studying to extract most worth from them.”
Leandro Perez
CMO for Australia and New Zealand at Salesforce
Leandro argues that the agentic AI shift isn’t essentially about creating totally new roles however somewhat about evolving current ones. With AI brokers dealing with routine duties, people will grow to be orchestrators of intelligence.
He emphasizes strategic considering, empathy, and resilience as expertise that may grow to be extra necessary with the involvement of AI brokers.
CX execs should evolve with AI
In keeping with Jason, CX groups should reskill in the same solution to advertising and marketing groups within the 2010s to scale back the associated fee to serve. “As search and social emerged as dominant channels for demand era, the “technical marketer” turned indispensable: half system integrator, half information analyst, and half advertising and marketing strategist,” he says.
CX will see the identical transition with the necessity for technical CX professionals who can design the foundational parts of AI brokers — information, insurance policies, procedures, and methods that help AI brokers. “They’ll then use qualitative and quantitative information to repeatedly enhance and optimize these methods,” he says, including that such expertise will command a premium within the job market.
As professionals adapt to this AI-driven shift, their roles will evolve somewhat than disappear. Nonetheless, with AI taking over extra duties, a urgent query emerges: what does this imply for the human workforce?
Is the menace to people actual?
Effectively, not likely.
Agentic AI can, in idea, operate autonomously and take over whole processes and methods. However will this integration be on the expense of human employees?
Employee issues about AI are each justified and misplaced, believes Kate O’Neill, founder and chief tech humanist at KO Insights. “The menace is not that AI will substitute people wholesale — it is that we’d fail to reimagine work in ways in which leverage uniquely human capabilities alongside AI.”
She claims that good corporations are already reframing AI from a substitute expertise to an enhancement expertise. “This is not simply semantic gymnastics; it is a basic shift in how we design and deploy these methods,” she provides.
“The way forward for work is not a zero-sum recreation between people and machines. It is about creating synergies that make each extra succesful, extra productive, and finally, extra human.”
Kate O’Neill
Founder and chief tech humanist at KO Insights
Kate calls upon AI agent distributors to design their instruments explicitly as human amplifiers, not human replacements. Meaning constructing instruments that improve human judgment, creativity, and emotional intelligence — the very qualities that make us uniquely human.
Stressing synergy, Sreelesh says essentially the most thrilling shift is not simply in creating new AI-specific jobs; it is in how AI transforms current roles into their “augmented” variations or the next-strategic evolutions of them.
He predicts that as agentic AI turns into extra widespread, we’ll see customer support representatives grow to be insight-driven engagement specialists, entrepreneurs grow to be buyer journey architects, and operations people grow to be automation strategists.
On the same be aware, Jason means that agentic AI will spawn extremely expert jobs unseen in CX thus far. These will concentrate on designing and creating the foundations that help AI brokers.
He claims that traditionally, human brokers have been requested to be the “glue” throughout methods and information sources — accumulating related information and navigating an internet of backend methods to resolve issues with orders, merchandise, and providers.
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Nonetheless, at this time, AI brokers related to information sources, methods, and instruments are enabling groups to automate these repetitive steps and concentrate on monitoring the standard and accuracy of responses, offering judgment on the following steps, and approving actions the place judgment is required.
As agentic AI evolves, each sellers and patrons should implement them in a human-centric method. Intrinsic motivation, a key driver for workers, can take successful if agentic AI is allowed to take over duties which have offered employees with a way of mastery and goal. It’s no extra about talent adaptation however reconstructing an expert id for employees as work will get divided between them and AI brokers.
Agentic AI can be sure to flatten conventional hierarchies inside organizations. Junior professionals armed with AI brokers can carry out at senior ranges, compressing years-long studying curves into months. This creates unprecedented workforce agility. As well as, senior professionals who’ve historically prided themselves on their info mastery should redefine their model.
The ethics and security hurdles
AI brokers work throughout methods. They don’t take breaks, go on trip, or want motivation to carry out duties. Ultimately, they’re tireless and timeless. How secure is buyer information with this novel utility of AI? And what ought to a governance framework for agentic AI seem like?
Within the film “2001: A House Odyssey,” the story of the autonomous robotic HAL 9000 takes an ominous flip. It goes rogue, doubting people, blaming them for errors, and disconnecting life help.
The destiny of people with agentic AI is unlikely to be comparable, at the least within the close to future. Earlier than the expertise turns into really autonomous, people should set up tips, verify for potential hallucinations, and defend information.
Agentic AI use: an influence play?
In keeping with Kate, essentially the most urgent moral issues round agentic AI transcend surface-level automation points to basic questions of belief and decision-making authority.
“The core moral problem round Agentic AI is not about algorithms or automation — it is about energy.”
Kate O’Neill
Founder and chief tech humanist of KO Insights
Who controls these selections? How can we guarantee prospects retain significant company?
“Each time an AI agent makes a selection, it is basically making a small prediction about human habits and desire. Get sufficient of those micro-decisions flawed, and we’re not simply failing at customer support — we’re undermining human autonomy. The stakes are larger than most corporations understand,” warns Kate.
The answer? We want unprecedented ranges of transparency with agentic AI. “Clients want to grasp not simply that they are interacting with AI, however how and why these brokers make particular selections,” suggests Kate.
Multi-system hallucinations may be actual
As we progress alongside the agentic AI gradient, brokers will work with one another.
In keeping with Tim, there are a couple of dangers to look at for when this occurs: they usually must trade credentials to truly carry out duties inside a multi-step course of. That might pose safety dangers as not all agentic platforms have the identical stage of trustworthiness.
“Reasoning errors (suppose hallucinations) have exponential affect as they unfold throughout agentic groups,” says Tim. “Consider how statements can get distorted as repeated throughout a series of human beings.”
Agentic options are safe, declare sellers
Responding to those issues, main AI agent sellers Salesforce and Zendesk declare their options function safety plug-ins past these historically deployed for AI instruments. They are saying people nonetheless management the wheel, buyer information is secure, and workplaces are metamorphosing into extra related and productive areas.
Salesforce
“Context is the king for correct, customized AI outputs,” says Leandro. “With out real-world information about your online business and your prospects, agent responses are generalized or, worse, depend on hallucinations and guesswork. Information is crucial, however so is its safe and moral dealing with.”
He explains that they developed the Einstein Belief Layer at Salesforce, which secures and anonymizes information to forestall leaks. “Transparency can be constructed into Agentforce. These with digital labor on their groups can simply evaluation the reasoning behind agent outputs and outline the scope of agent tasks in pure language,” he provides.
Zendesk
In Zendesk’s case, the human-in-the-loop strategy is integral to utilizing agentic AI.
Jason explains the strategy and says they’ve configurable thresholds that permit human brokers or directors to evaluation and approve AI-generated content material and recommended actions.
“Any high-risk motion, like issuing refunds or making account modifications, may be configured to at all times have a human operator evaluation and ensure it,” he provides.
Amplify human potential, not simply automate duties
As for governance round AI brokers, Kate says, “Cease ready for excellent rules — they will not come. As an alternative, construct governance frameworks that put human outcomes first.”
“Sure, doc your processes. Sure, set up clear accountability. However the actual work is creating methods that amplify human potential somewhat than simply automate human duties.”
“Your ethics board ought to seem like your buyer base, not your government group. Deliver within the skeptics, the philosophers, the social scientists — and most significantly, representatives from the communities your AI methods will have an effect on.”
Kate O’Neill
Founder and chief tech humanist at KO Insights
She believes that the businesses that thrive will not be those with essentially the most refined AI — they’re going to be those who constructed essentially the most considerate guardrails round it.
AI or human: study when to modify gears
The important thing talent of the longer term is not writing prompts or managing AI — it is the power to collaborate with AI to resolve more and more complicated challenges, believes Sreelesh.
Marshall McLuhan, a Canadian communications theorist, was prescient in his statement when he mentioned, ‘We form our instruments, and thereafter, our instruments form us.”
That is precisely what’s taking place with AI. We have created these instruments to boost our capabilities, and now they’re reshaping how we work, suppose, and resolve issues, says Sreelesh. It’s altering how intelligence itself operates throughout organizations.
Having essentially the most superior AI will not assure success — what’s going to set organizations aside can be their capacity to steadiness human and synthetic judgment prudently.
This requires creating a solution to orchestrate human intelligence and feelings into agentic AI-driven decision-making processes. This is not going to solely delight prospects however assist improve worker expertise.
With inputs from Yukta Rustagi, Matthew Miller, and Brett Nehls of G2.
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Edited by Supanna Das
