How AI agents will transform your customer service – despite 3 hurdles


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ZDNET’s key takeaways

  • Service leaders see investment in AI agents as essential to meet business demands.
  • Conversational AI is reshaping customer communication across digital channels.
  • AI field service investments will significantly increase over the next year.

Nearly 8 out of 10 service leaders say investment in AI agents is essential for meeting business demands, according to the 2026 State of Service report from Salesforce. The report’s seventh edition surveyed 6,500 service professionals across 40 countries and five continents, including service vice presidents, directors, and team leaders.

Also: Moving from AI pilots to business-wide value requires a superhighway – how to ramp up

Here is the executive summary of the key findings: 

  1. Teams tackle AI adoption challenges: Service teams face challenges such as meeting customer demands with limited resources, talent shortages, and successfully implementing AI. However, companies that have integrated their service channel data into a unified platform are 1.4x more likely to rate their AI implementation as very successful than those with siloed systems.
  2. AI agents redefine customer service: Companies are incorporating predictive, generative, and agentic AI to deliver faster, more accurate, and more personalized interactions. Leaders expect AI agents to amplify prior AI outcomes and are backing that expectation with investment. Seventy-nine percent  of service leaders say investing in AI agents is essential to meeting business demands.
  3. AI gets conversational with voice and multimodal interactions: Conversational AI is reshaping customer communication across digital channels, like text and chat, increasing self-service resolution rates. When cases do need human attention, the right AI tools maintain context. Eighty-five percent of service professionals with voice AI say customer transitions to human representatives are seamless. 
  4. Agentic AI makes field service safer and more efficient: Field service organizations face inefficiencies caused by administrative tasks, scheduling issues, and long wait times for parts. AI can help. Eighty-five percent of field service leaders believe their AI field service investments will increase over the next year.

Also: Why business architects are poised to lead the corporate AI revolution

Here are the top 10 key takeaways of the State of Service 2026 report: 

AI adoption challenges 

  1. Customer service demands are growing faster than expected. The research shows that 82% of service professionals agree that customer expectations are higher than they used to be. And customers expect a lot, from 24/7 support to tailored interactions. And though 81% of service representatives say building relationships with customers is an important part of their job, they spend less than half their time (46%) with customers due in part to administrative tasks and internal responsibilities. The pressure of excellent service is real – 43% of consumers say a poor customer service experience will prevent them from making a repeat purchase.
  2. Talent shortages prevent customer service from leveraging AI agents. Attrition is an obstacle: 12% of service employees left their companies over the past year, and these highly trained individuals are often hard to replace. Top service challenges include keeping up with changing customer expectations, high operational costs, and difficulty hiring and retraining employees. 
  3. Security concerns hold back AI adoption. Service leaders cite security concerns as their top challenge while implementing AI, and over half say it’s delayed or limited these initiatives. The research found that 75% of IT security leaders believe AI-driven cyber threats will soon outpace traditional defenses.

Also: 96% of IT pros use AI now: Their top 7 agentic applications and biggest implementation roadblocks

AI agents reshape customer service 

  1.  AI adoption comes in multiple forms of capabilities, each progressively harder to implement. Companies are investing in all three forms of AI: predictive, generative, and agentic. Sixty-nine percent of service professionals say their organization uses at least one form of AI, with 39% reporting the use of agentic AI. Only 6% of service leaders don’t expect to use agentic AI within five years — a finding that makes sense, given that 79% say AI agent investment is essential to meet business demands. The timelines noted are much longer than they should be. All businesses should have agentic AI capabilities by 2027. It is difficult for companies to deliver value at the speed of need without AI agents, especially when customers will use them to engage. 
  2. AI agents are delivering measurable results today. Service ops and leaders who use AI agents expect their service costs and case resolution times to decrease by an average of 20%. At Salesforce, AI agents have answered nearly 4 million cases with satisfaction, including support for web, phone, and app channels. In addition to cost savings, AI agents deliver 20% faster resolution times, 20% less wait time, 18% more case deflections. 
  3. Humans and AI agents can do more together, faster and better. The report found that collaboration between humans and AI in customer service yields significant benefits. In fact, 83% of service representatives at organizations with AI say they have better career prospects because of it, and 82% say working with AI has helped them develop new skills. It’s also made them more productive and their jobs less stressful.

Also: AI project stalled? Blame your outdated, fragmented workflow – and redesign it now

AI agents are conversational and can deliver multimodal interactions

  1. Customers are talking more with AI agents. Multimodal AI is technology that can handle different types of input — voice, text, chat, and visual — within a single system. AI agents are turning these touchpoints into natural-language conversations. Already, 36% of organizations with both voice and text AI have integrated these modes.
  2. The benefits of conversational AI are realized by both customers and companies. Conversational AI works best when it’s built on your organization’s data — ensuring it delivers accurate answers while maintaining your brand voice and tone. It also taps into customer data to personalize every interaction — speaking their language, matching their tone preferences, and adapting to their communication needs. Research found that 89% of context is maintained when customers move from voice AI to human reps. 
  3. AI agents are getting much better at understanding humans. The research found that 88% of companies said they are good or excellent at maintaining a consistent brand voice. However, there’s still room for improvement across the board. While 35% of service professionals say their AI is excellent at understanding emotions, others are less impressed. This represents a major leap toward making AI interactions feel truly natural.

The State of Service report also found that field service organizations are realizing great productivity gains by using AI agents. According to the report, 37% of technicians said admin tasks keep them from doing their actual jobs, and they spend an average of 7.27 hours per week on low-value tasks. Technicians said AI could tackle 35% of admin work, freeing up two hours a week. Eighty-eight percent report at least a moderate improvement in technician utilization, and 85% report at least a moderate improvement in dispatcher productivity. The report noted that 85% of field service leaders believe their AI investments will increase over the next year.

Also: The rise and risks of agent management platforms

AI agents are transforming customer service, and agentic maturity is creating customer journeys from good to great. To learn more about the State of Service 2026 Report, you can visit here





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Digital Evidence Has Reshaped Criminal Defense – and the Defense Bar Is Still Catching Up

A decade ago, a felony case file might have run to a few hundred pages of police reports, witness statements, and lab results. Today, that same case can include a full cell phone extraction, hours of body-worn camera footage, surveillance video from multiple cameras, social media exports, license-plate-reader hits, and digital forensic reports running thousands of pages. The substantive law has not changed nearly as fast as the evidence it operates on.

For criminal defense practitioners, the shift is not just about volume. It is about how cases are investigated, how discovery is reviewed, how plea calculations are made, and how trials are tried. A defense lawyer who treats digital evidence as an afterthought — to be skimmed close to trial, with the cell phone dump opened only if something obvious surfaces — is no longer providing competent representation in most serious cases.

The Volume Problem

Modern law enforcement investigations generate digital evidence at a scale that traditional defense workflows were never designed to handle.

A single cell phone extraction using forensic tools commonly used by prosecutors can produce a report tens of thousands of pages long. Multiply that across co-defendants. Add cloud account data subpoenaed from providers. Add body-cam footage from every responding officer, often running an hour or more per officer per incident. Add interview recordings, surveillance video, ALPR records, and any wiretap or pen register data.

The defense lawyer’s obligation is to review all of it — or at least to review it competently enough to identify what matters. Doing that without a workflow is impossible. Cases get lost not because the exonerating evidence was hidden, but because it was buried in the third week of message history nobody had time to read.

The practical response involves a combination of technology and process: e-discovery review platforms scaled for criminal cases, paralegal-level review with defined search protocols, and clear allocation of which categories of evidence the attorney personally reviews versus which are screened first. Firms that handle digital-evidence-heavy cases without that infrastructure tend to discover, late in the process, that something important was missed.

Authentication and Chain of Custody Have Become Central

Volume is half the problem. The other half is that digital evidence is harder to authenticate than the physical evidence it has displaced.

A surveillance video recovered from a business has to be tied to a specific camera, on a specific system, with verified timestamps, with continuous custody from the moment of seizure to the moment of presentation. A cell phone extraction has to be tied to a specific device, performed using a documented forensic process, with hash values demonstrating that the data has not been altered. A social media export has to be authenticated either through the provider’s certification or through circumstantial evidence connecting the account to the defendant.

Each of these chains has potential breaks. Cameras get the wrong time. Forensic extractions get performed with outdated software. Social media accounts get used by people other than the registered user. Defense counsel who understands the technical underpinnings of how evidence was collected can identify gaps that opposing counsel may have assumed were settled.

Federal procedure in particular has evolved around these issues. Practitioners working in federal court should be familiar with the Federal Rules of Evidence governing authentication and the best-evidence rule, both of which apply to electronic records in ways that often surprise lawyers more accustomed to paper-era practice.

Discovery Obligations and the Brady Problem

The growth of digital evidence has also complicated the prosecution’s obligations under Brady and its progeny, which require disclosure of material exculpatory and impeachment evidence to the defense.

When the relevant evidence universe was a few hundred pages, prosecutors could reasonably review the file and identify Brady material. When the universe is a hundred thousand pages of cell phone data and dozens of hours of video, identifying what is exculpatory becomes a much harder problem — and not always a problem prosecutors solve well. Defense counsel cannot rely on the prosecution to flag what the defense will find useful. The defense has to find it themselves, which loops back to the volume problem.

Courts have been inconsistent in how they handle Brady obligations in the digital age. Some jurisdictions require prosecutors to provide searchable, organized productions; others permit document dumps that effectively shift the search burden to the defense. The practical implication is that defense lawyers in serious cases must budget significantly more time for discovery review than would have been required even a few years ago, and must do so on schedules that prosecutors and courts often have not adjusted to reflect the new reality.

How Digital Evidence Changes Plea Negotiations

Plea negotiations have always been driven by each side’s assessment of trial risk. Digital evidence has changed both sides of that calculation.

For the prosecution, video and digital records often appear to lock in factual elements that previously turned on witness credibility. A clear video of an alleged assault, or a series of incriminating messages, can shift a case from a battle of testimony into a battle of interpretation. Prosecutors evaluating cases with strong digital evidence often offer less, because they perceive their trial position as stronger.

For the defense, the same evidence frequently contains nuance that changes how a jury would actually receive it. Body-cam footage that the prosecution thinks is damning often shows context that supports the defense theory. Cell phone messages read in full rather than excerpted often tell a different story. The defense lawyer who has actually watched the video and read the messages — rather than relying on the prosecution’s characterization — is often in a meaningfully stronger negotiating position than the case file would initially suggest.

This is part of why pretrial preparation has become more decisive. The cases that resolve favorably are usually the cases where the defense did the digital evidence work early enough to see what was actually there, rather than what the police reports said was there. Resources from the California Courts and the State Bar of California outline the procedural framework within which this work has to happen, but the framework alone does not produce results — sustained attention to the evidence does.

What Effective Defense Looks Like Now

Competent criminal defense in 2026 looks different than it did even five years ago. The lawyers who get the best outcomes for clients tend to share a few characteristics: they take digital evidence seriously from intake forward, they have the infrastructure to review it at scale, they understand the technical questions well enough to challenge authentication where appropriate, and they treat plea calculations as something to be made after the evidence has been examined rather than after the police reports have been read.

For people facing serious charges in California, the practical implication is that the choice of counsel matters more, not less, in the digital evidence era. A firm like Angelo Reyes Law, built around trial-ready preparation rather than volume-driven plea processing, reflects what effective representation tends to look like in cases where the evidence record is large and where the difference between a good and a poor outcome turns on what defense counsel actually finds in the file.

The volume of evidence will keep growing. Defense practice has to keep up.



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