Key Takeaways
- The future of law enforcement is increasingly defined by the ability to move from siloed data systems to intelligence that can support police dispatch decision-making
- New technology in law enforcement is expanding access to data, but the real challenge is identifying what is relevant and actionable during active incidents
- Real-time crime response depends on delivering trusted, accurate, verified data that supports dispatch decisions rather than overwhelming them
- Business crime trends are becoming more coordinated and widespread, creating new challenges and driving continued advancement in law enforcement technology
- Public-private collaboration is essential to delivering verified intelligence directly into police dispatcher workflows
THE FUTURE OF LAW ENFORCEMENT: WHAT TO EXPECT IN 2026
The future of law enforcement is being shaped by rapid advancements in technology, including AI. At the same time, an evolving information landscape is making it more difficult for agencies to determine what can be trusted during active incidents.
Like other sectors, law enforcement is undergoing rapid transformation as agencies work to address emerging crimes, public safety risks, and escalating violence. While agencies have access to more data than ever before, the central challenge remains determining what information represents actionable intelligence. Despite this, a gap remains between the volume of available data and what can actually be used by dispatch during an active incident.
Five emerging trends, in particular, are prompting agencies to reimagine the future of law enforcement and operational response.
1. ADVANCES IN POLICE TECHNOLOGY AND MODERN POLICING
Technology advancements like artificial intelligence (AI) and predictive analytics are expanding access to data and helping agencies manage workload and operational demands. However, they also contribute to a growing challenge: operational data overload.
AI is increasingly used to relieve administrative burden and staffing pressures. A 2025 U.S. Public Safety Trends Report found that 76% of officers spend more than half of their shifts on paperwork, with 70% relying on overtime to complete administrative tasks. It’s no surprise that there is widespread support for AI adoption.
Law enforcement leaders are using AI to:
- Automate report writing and reduce time spent on paperwork
- Generate investigative summaries more quickly
- Streamline video and data review
These operational efficiencies offer the promise of optimizing a law enforcement labor pool that is already understaffed. However, unanswered questions around privacy, accuracy, and legal defensibility continue to limit broader reliance on AI.
Similarly, predictive analytics has the potential to streamline operational functions. This capability is expected to support operational functions such as:
- Optimize vehicle fleet management through data‑driven maintenance projections
- Inform resource allocation models based on anticipated demand
- Combine historical crime data with real‑time traffic patterns and contextual variables
- Produce forecasts of crime patterns to guide routing and deployment strategies
At the same time, these systems also introduce challenges by generating forecasts, correlations, and probability-based outputs, increasing the volume of data that must be vetted. In addition, crime patterns are inherently variable and not always predictable, particularly when violence escalates unexpectedly. In these scenarios, predictive analytics alone may be insufficient to support operational decisions. Real-time verified intelligence becomes critical, as decisions must be based on what is actually occurring rather than what a model anticipates.
Larger, more complex flows of analytical output therefore reinforce an existing challenge for law enforcement dispatch and response teams: determining which inputs are verified, relevant, and actionable during active incidents. As analytical capability increases, so does the risk of uncertainty if predictive outputs are treated as intelligence rather than data. This underscores the need for mechanisms that validate and filter information before it reaches police dispatch, ensuring technology supports responding officers’ decision-making in critical moments rather than overwhelming it.
2. REAL-TIME CRIME RESPONSE AND DISPATCH INNOVATION
The introduction of real‑time crime centers (RTCCs) marks an important evolution in modern policing by improving visibility and access to data during incidents. They have helped establish the importance of real-time intelligence in understanding and managing crimes in progress. This reliance introduces limitations, as RTCCs are often dependent on analysts to identify, request, correlate, and interpret data during an active event. In many cases, intelligence from impacted businesses or external security systems is not directly available and must be requested at the time of the incident. This introduces additional steps during critical moments and can limit what is immediately visible within the RTCC environment.
The next evolution in real-time crime response is the ability to deliver verified, dispatch-ready intelligence directly into police dispatch workflows while an event is in progress. This shift reflects a broader need to ensure that intelligence is not only available, but usable at the point of dispatch. In this direct to dispatch model, intelligence is validated for accuracy and relevance before it reaches police dispatch, where it can be reviewed and shared with responding officers.
RTCCs continue to play a critical role by providing deeper analysis, broader situational awareness, and ongoing investigative support. 3Si’s DirectToDispatch™ complements this role by ensuring that confirmed crime events with verified actionable intelligence are delivered directly to the police dispatch center in real-time, without requiring law enforcement to request and assemble external data during an active incident. This approach helps close the gap between detection and dispatch by ensuring that only verified, relevant intelligence is delivered when it is needed most.
DirectToDispatch™ is agency agnostic, 24/7/365, and supports law enforcement agencies with or without an RTCC. The capability is enabled by the private-sector organization confirming the crime and sharing verified video and other intelligence without requiring investment or operational burden from law enforcement.
Together, this approach strengthens how real-time intelligence is used across the response continuum, supporting more informed decision-making while preserving existing workflows and law enforcement control.
3. THE GROWING IMPACT OF BUSINESS AND FINANCIAL CRIME TRENDS
Emerging business crime trends present a growing and complex challenge for security teams and law enforcement. A surge in crimes such as organized retail crime (ORC), cargo and supply chain theft, ATM theft and rising threats against corporate executives explains why business theft is increasing. These crimes strain private sector security and public safety resources.
Key business crime trends impacting law enforcement include:
- ORC that is carefully coordinated, highly resourced and increasingly violent
- Cargo and supply chain theft, which continues to rise and carries significant enterprise security risks
- Escalating threats of violence against corporate executives
- Growing instances of ATM jackpotting with an estimated 700 attacks in 2025 resulting in more than $20 million in losses
According to the National Retail Federation’s 2025 Impact of Retail Theft and Violence Report, 46% of retailers reported an increase in violence against employees or customers during criminal incidents, while 48% saw a rise in cargo and supply chain theft. At the executive level, 42% of security leaders across industries reported a significant increase in threats of violence against company executives.
In response, both public and private investigation teams are adopting more targeted, intelligence‑led strategies focused on scale and coordination, including:
- Specialized ORC task forces dedicated to investigating organized theft networks
- Expanded use of technology, such as license plate readers (LPR) and facial recognition, to identify offenders across locations
- Stronger partnerships with federal agencies, including Homeland Security Investigations (HSI) and the FBI, to address crimes that cross jurisdictional and state borders
- Stricter state‑level legislation aimed at prosecuting perpetrators of ORC
Combating business crime now requires coordinated enforcement strategies, public‑private collaboration and data‑driven investigations. Collaborative advancements are increasing but forging effective partnerships takes time and education of all parties.
4. PROTECTING DISTRIBUTED BUSINESS LOCATIONS AT SCALE
Protecting distributed business locations at scale — such as national retail chains, convenience stores and financial institution branches — has become one of the most complex challenges facing law enforcement today. These environments create unique vulnerabilities that organized criminal groups are quick to exploit.
Key challenges law enforcement faces include:
- Fragmented infrastructure and inconsistent security standards across locations increase enterprise security risks
- ORC rings that coordinate smash‑and‑grab incidents and flash‑mob thefts at multiple sites in rapid succession
- Jurisdictional silos that make it difficult to recognize patterns or connect related incidents across cities and states
- Financial crime against ATMs is transitioning from brute force attacks on equipment to “jackpotting,” sophisticated cyber-physical crime where criminals install malware or hardware that forces machines to dispense cash.
Unlike isolated shoplifting cases, ORC incidents are well planned and deliberately distributed, making broader visibility essential to effective prosecution. To address these challenges, law enforcement agencies are shifting toward collaborative, intelligence‑led approaches designed to protect multiple locations at once. These efforts increasingly focus on:
- Public‑private partnerships, such as the Coalition of Law Enforcement and Retailers (CLEAR), to improve information sharing and disrupt organized networks earlier
- Security systems that aggregate video and other security data across entire enterprises rather than treating incidents in isolation
- Real-time intelligence platforms that allow businesses to share critical intelligence with law enforcement during incidents without giving direct enterprise system access
- Analytics‑driven insights that surface trends, link related events and support faster, more coordinated investigations
Together, these strategies are improving visibility across distributed environments. However, the ability to deliver verified, actionable intelligence to dispatch during active incidents remains critical to empowering police for optimal response on the scene.
5. COLLABORATION BETWEEN LAW ENFORCEMENT AND THE PRIVATE SECTOR
Collaboration in law enforcement is evolving from informal coordination to real‑time, technology‑enabled partnerships across dispatch, command staff, analysts and external partners. Intelligence sharing platforms are breaking down silos, enabling business security teams to collaborate with public safety during incidents using verified video and other data to address situations while in progress rather than after the fact.
When incidents occur, access to detailed intelligence can significantly improve outcomes, including:
- Shared, real‑time operational intelligence that allows dispatchers, analysts and command staff to act from the same verified information
- Validated intelligence delivered during incidents, enabling informed decisions before officers arrive on scene
- Coordinated response across teams and jurisdictions through integrated platforms rather than siloed systems
- More confident decision‑making that improves officer safety, response effectiveness and resource allocation
This shift creates challenges around data governance, training and accountability, as more roles rely on live intelligence for operational decisions. At the same time, a limited law enforcement labor force is pushing officers to the limits, elevating the importance of effective collaboration with the private sector to jumpstart investigations, surface actionable intelligence earlier and alleviate some of the investigative burden on police officers. This matters because strong collaboration can improve officer safety and decision confidence, while weak or fragmented collaboration can undermine the value of advanced technology investments and further strain already limited personnel.
HOW BUSINESS CRIME IS DRIVING POLICE TECHNOLOGY ADVANCEMENTS
Emerging business crime trends are reshaping law enforcement future technology priorities by exposing gaps in traditional response models. Crimes such as organized retail crime, coordinated flash‑mob thefts, cargo theft and threats against distributed business locations move faster, span wider geographies and involve higher levels of coordination than conventional incidents. These patterns demand police technology advancements driven by business crime trends, not just incremental upgrades to legacy technologies. Law enforcement agencies are increasingly adopting real‑time intelligence platforms, advanced analytics and integrated command‑and‑control systems to gain visibility across multiple locations and jurisdictions simultaneously. However, security intelligence from private sector security team is required as well to address emerging crime trends like ORC, financial crimes and supply chain theft, which largely occur in the confines of private business locations.
Technologies that can help security teams and dispatch validate crimes in progress and deliver verified, dispatch‑ready intelligence are becoming essential to countering highly mobile, organized threats and to protecting officers in increasingly volatile situations. As business crime continues to evolve, law enforcement must pair new tactics with scalable, intelligence‑led technologies that support proactive, informed responses.
POLICE TECHNOLOGY ADVANCEMENTS AND THE FUTURE OF LAW ENFORCEMENT
As law enforcement looks ahead to 2026, the future of policing is increasingly defined not by access to more data, but by the ability to transform fragmented information into unified, dispatch‑ready intelligence. Business crime trends are driving police technology advancements, pushing agencies to adopt tools that expand visibility while also introducing new challenges around data volume, governance and validation. Advances in AI, predictive analytics, and real‑time crime response are reshaping operations, but their value depends on ensuring intelligence supports dispatch decision‑making rather than overwhelming it. At the same time, public‑private collaboration is becoming essential to closing information gaps by securely delivering verified intelligence directly into dispatcher workflows. DirectToDispatch™ technology supports more informed on-site response, improves officer safety in the field, and strengthens prosecution outcomes.
Learn more about this technology and how it supports law enforcement response. Visit DirectToDispatch™ page.
FAQs
What is the biggest challenge in real-time crime response today?
The biggest challenge in real‑time crime response today is turning overwhelming volumes of live data into verified actionable intelligence to support dispatch decisions. Law enforcement agencies, particularly dispatchers, must process and validate information from sources such as alarms and emergency calls in order to prioritize response and deploy limited resources effectively. To effectively respond to an incident, police require access to verified, actionable intelligence, making real‑time video and data available in a way that supports informed decisions without requiring dispatchers or officers to sift through vast amounts of information or rely on unverified reports.
Why doesn’t more data always improve law enforcement response?
More data doesn’t always improve law enforcement response because volume can overwhelm decision‑making during active incidents. AI, sensors, video and external data sources generate vast amounts of data, but not all of it is timely, accurate or actionable. Without validation, excess data can slow dispatch decisions and increase uncertainty. Effective response depends on transforming raw inputs into verified, dispatch‑ready intelligence, delivering the right information to officers on the scene at the right moment.
Why are organized retail crime and other business crime trends a growing concern for law enforcement?
Organized retail crime (ORC) and related business crime trends are increasingly coordinated, often violent and frequently span multiple jurisdictions. Beyond traditional theft, law enforcement now faces challenges such as coordinated flash‑mob incidents and crimes targeting distributed business locations like retail chains, convenience stores and financial branches. These crimes strain police resources, require visibility across locations and jurisdictions, and demand specialized task forces, advanced technology, and strong partnerships with private businesses and public safety to effectively disrupt organized criminal networks.
Why are public-private partnerships critical to the future of law enforcement and private sector intelligence?
Public‑private partnerships provide law enforcement with timely, detailed intelligence that is often unavailable through traditional reporting methods. The controlled sharing of information collected by enterprise security systems, such as video evidence, tracking data and real‑time alerts improves investigations, enhances officer safety, and supports more informed, effective responses, particularly during crimes in progress.
Sources:
Matt Kushner, CEO
Charlie Erickson
Ben Tucker
Mary Pifer
