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The pros, cons, and best practices when it comes to using generative AI

Colin Redbond, SVP Product Management, SS&C Blue Prism

We’ve all heard about growing interest in generative AI, especially following the release of ChatGPT. The artificial intelligence (AI) large language model, and ones like it, have the potential to revolutionize business operations and accelerate digital transformation journeys. Those that get ahead of this trend are set to gain a significant competitive advantage, with generative AI showing no signs of disappearing anytime soon.

While historically, AI projects have been long, expensive, and complex, generative AI has the potential to reduce time to value for digital transformation initiatives and make advanced technologies more accessible to a greater cross section of people thanks to its ease of use and learning capabilities.

How generative AI supports digital transformation

Digital transformation initiatives went into hyperdrive following the pandemic, but most organizations have yet to maximize business outcomes with their current automation plans. Intelligent automation combines technologies, like generative AI, robotic process automation (RPA), business process management, etc., to reengineer processes and drive business outcomes.

So, what’s the value of generative AI? Its range of capabilities and accessibility is unprecedented, marking an exciting time for the automation space and any sector standing to benefit from advancements in natural language processing, including healthcare, finance, and customer service. However, generative AI is still limited, in a sense, to its own domain knowledge. 

When you combine its unique capabilities with the power of intelligent automation, the impacts for digitalization are extraordinary. Generative AI can be used to automate tasks that were previously only possible for humans to perform, such as generating new marketing copy, designing new product prototypes, or creating personalized content for each customer. It can suggest automations and enable a greater cross section of workers to initiate the development of automations thanks to its ease of use. Automations can then be designed within designated governance parameters and best practices.

By automating these tasks, employees can reduce their workload, supporting work-life balance, while also increasing their efficiency, reducing company-wide costs, and improving the accuracy and quality of their output. Employees work with generative AI to deliver superior results.

When it comes to creative work, humans add color and empathy, which technology can only try to mimic. Generative AI gives them a starting point, helps with idea generation, etc. Human workers provide their uniquely human abilities to read between the lines and their emotional empathy for which AI is not substitute.

For many people, when they think “generative AI,” they think about written content or even AI art, but the use cases for generative AI relate to the day-to-day operations of most office workers.

For example, automated emails can exhibit a greater degree of personalization and improve resolution times. For more complex or high-level emails, generative AI can be used to draft an adequate, personalized email, with all needed information, and a human can then review and tweak if needed.

A similar process can unfold with contact center processes, generative AI bots can progress customer communications significantly before needing to loop in a human employee – if they need to be looped in at all for simple enquiries. This ensures human employees’ time is used effectively and as many customers as possible are being serviced, especially with generative AI bots being able to work around the clock. Error handling is improved with error messages providing context that enables immediate resolution.

Intelligent document processing (IDP) solutions, which use a combination of optical character recognition and AI to extract information that is locked away in documents, are enhanced by generative AI capabilities. This is especially important for financial and healthcare services. Generative AI’s understanding and learning features better equip it to contend with unstructured data, an area that has been a weak point for IDP solutions, which have been confined to structured and semi-structured documents at best.

Generative AI can also help improve the overall performance of intelligent automation systems by allowing them to adapt and learn over time by analyzing the results of previous tasks and using that data to generate new content or output.

The need for governance and risk management to unlock the potential of AI

However, businesses need to make certain considerations before they explore adding generative AI to their toolkit to accelerate digital transformation, since its outputs can have a significant impact on a company’s reputation, revenue, and legal liabilities. A clearly defined corporate governance risk management strategy and set of operating principles around this need to be developed. Done right, generative AI can support an automation strategy that is even more innovative, cost-effective, and productive than anything we have seen before.

Reasons why governance and risk management considerations are important when using generative AI:

  • Help ensure AI-generated content does not violate intellectual property, privacy, or other laws
  • Make sure use of generative AI aligns with your organization’s ethical principles
  • Maintain your organization’s quality standards and confirm outputs are consistent with expectations
  • Ensure the right information is used for the right purposes to protect sensitive information and privacy

How to develop a governance and risk management strategy

A clearly defined strategy and concomitant operating principles maximize the benefits of generative AI while mitigating any outfall. Developing a strategy involves several key steps:

  1. Define the scope: This includes the types of content you will be generating, the data you will be using, and the intended use cases for the content. This helps with identifying the specific risks and governance requirements that apply to your initiatives.
  2. Identify risks: These may include legal risks such as infringing on intellectual property, ethical risks such as bias in generated content, and security risks such as the potential for data breaches. You may need to engage with legal and compliance experts to identify all potential risks.
  3. Establish governance requirements: Based on the risks you’ve identified, establish governance requirements that will mitigate those risks. These may include policies and procedures for data handling, content review, and compliance with regulations.
  4. Develop a risk management plan: Outline how your organization will mitigate and manage risks. This may include risk assessments, monitoring, and regular reviews of governance practices, as well as processes for identifying and addressing any issues that arise.
  5. Train employees: It’s important to train employees on governance and risk management practices. This may include training on data handling, content review, and compliance with regulations. Make sure all employees who will be working with generative AI understand the risks and their responsibilities for mitigating those risks.
  6. Monitor and review: Monitor and review your governance and risk management practices on an ongoing basis. This will help you identify any gaps or issues that need to be addressed and ensure that your practices remain effective over time.

Like all advanced technologies, generative AI’s impact is positive – so long as you take the steps necessary to ensure you’re using it the right way. There’s no turning back the train, generative AI is here to stay – full steam ahead. The best approach is going to be to embrace it with care and work with providers when it comes to decision making around implementation. The possibilities behind generative AI are exciting – so let’s work to get it right and make it a force for good.

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AI and GenAI tools can add business value – but the right skills are vital to make this possible

Source: Finance Derivative

Faye Ellis, Principal Training Architect – AWS at Pluralsight

Generative AI has captured the imagination of many over the past year. However, aside from using ChatGPT to write our wedding speeches and do our kid’s homework, there are many ways to maximise the technology to add real business value and a competitive edge.

Getting the right skills in place for employees is also key for businesses. Whether employees are total beginners to AI or looking to move into advance uses, investment in the technology will only bring true business benefits if people are empowered to work with it effectively, try new applications, and do so securely.

Here are four examples of where AI, when used well, can bring real business value:

Build your own chatbots

Conversational chatbots and virtual assistants can increase customer engagement in an interactive and personalised way. They can be tailored to reflect brand voice, and be delivered in a consistent way across a site so customers always have access to timely support.

Amazon Lex, for example, makes it easy to build high-quality conversational interfaces powered by generative AI. 

Automate your repetitive business processes

Generative AI is ideal for automating repetitive tasks that don’t require high levels of creativity, such as reviewing and summarising contracts, generating project collateral, and code documentation. FAQ engines that handle common customer support and HR inquiries are expected to become commonplace. Marketing teams that need to develop campaigns in a similar style to previously successful campaigns, or automate customer outreach, will also find that they can easily automate these repetitive tasks with generative AI. 

Content marketers can use services like Bedrock to build a social media campaign for a new product or service. Marketers provide relevant data and prompts, and Bedrock generates copy and images for targeted social media posts. 

Incorporate generative AI into your cybersecurity

Generative AI can be used in risk modelling and assessing and interpreting the risk of cybersecurity incidents and findings.

Use generative adversarial networks (GANs) to create synthetic data, enabling security experts to anticipate what might happen during a cyber attack

Generate image, video, and text

Most of us are familiar with image, video, and text generation—the primary capabilities of generative AI. Use cases include creating original content, images, and summarising text.

Leading pre-trained AI models are available through SageMaker and Bedrock to help you get started quickly. Use Bedrock Chat Playground to experiment with various models using a chat interface.  

Getting your teams up to speed with AI

To start using these technologies, you need your staff to be skilled in using them.

Organisations might be accelerating AI adoption, but employees need the right skills – otherwise organisations risk facing an AI literacy gap. In fact, our recent research found that 80% of executives currently neglect employee training, and 20% don’t have an understanding of their teams’ AI skills.

By focusing on training the existing talent pool, it’s possible to propel them through the next wave of AI innovation, and fill talent gaps from within.

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How can businesses make the cloud optional in their operations?

Max Alexander, Co-founder at Ditto

Modern business apps are built to be cloud-dependent. This is great for accessing limitless compute and data storage capabilities but when connection to the cloud is poor or shuts down, business apps stop working, impacting revenue and service. If real-time data is needed for quick decision-making in fields like healthcare, a stalled app can potentially put people in life-threatening situations.

Organisations in sectors as diverse as airlines, fast food retail, and ecommerce that have deskless staff who need digital tools accessible on smartphones, tablets and other devices to do their jobs. But because of widespread connectivity issues and outages, these organisations are beginning to consider how to ensure these tools can operate reliably when the cloud is not accessible. 

The short answer is that building applications with a local-first architecture can help to ensure that they remain functional when disconnected from the internet. But then, why are not all apps built this way? The simple answer is that building and deploying cloud-only applications is much easier as ready-made tools for developers help expedite a lot of the backend building process. The more complex answer is that a local-first architecture solves the issue of offline data accessibility but does not solve the critical issue of offline data synchronisation. Apps disconnected from the internet still have no way to share data across devices. That is where peer-to-peer data sync and mesh networking come into play.

Combining offline-first architecture with peer-to-peer data sync

In the real world, what does an application like this look like?

  • Apps must prioritise local data sync. Rather than sending data to a remote server, applications must be able to write data using its local database in the first instance, and then listen for changes from other devices, and recombine them as needed. Apps should utilise local transports such as Bluetooth Low Energy (BLE) and Peer-to-Peer WiFi (P2P Wi-Fi) to communicate data changes in the event that the internet, local server, or the cloud is not available.
  • Devices are capable of creating real-time mesh networks. Nearby devices should be able to discover, communicate, and maintain constant connections with devices in areas of limited or no connectivity.
  • Seamlessly transition from online to offline (and vice versa). Combining local sync with mesh networking means that devices in the same mesh are constantly updating a local version of the database and opportunistically syncing those changes with the cloud when it is available.
  • Partitioned between large peer and small peer mesh networks to not overwhelm smaller networks if they try to sync every piece of data. In order to do this, smaller networks will only sync the data that it requests, so developers have complete control over bandwidth usage and storage. This is vital when connectivity is erratic or critical data needs prioritising. Whereas, the larger networks sync as much data as they can, which is when there is full access to cloud-based systems.
  • Ad-hoc to enable devices to join and leave the mesh when they need to. This also means that there can be no central server other devices are relying on.
  • Compatible with all data at any time. All devices should account for incoming data with different schemas. In this way, if a device is offline and running an outdated app version, for example, it still must be able to read new data and sync.

Peer-to-peer sync and mesh networking in practice

Let us take a look at a point-of-sale application in the fast-paced environment of a quick-service restaurant. When an order is taken at a kiosk or counter, that data must travel hundreds of miles to a data centre to arrive at a device four metres away in the kitchen. This is an inefficient process and can slow down or even halt operations, especially if there is an internet outage or any issues with the cloud.

A major fast-food restaurant in the US has already modernised its point of sale system using this new architecture and created one that can move order data between store devices independently of an internet connection. As such, this system is much more resilient in the face of outages, ensuring employees can always deliver best-in-class service, regardless of internet connectivity.

The vast power of cloud-optional computing is showcased in healthcare situations in rural areas in developing countries. By using both peer-to-peer data sync and mesh networking, essential healthcare applications can share critical health information without the Internet or a connection to the cloud. This means that healthcare workers in disconnected environments can now quickly process information and share it with relevant colleagues, empowering faster reaction times that can save lives.

Although the shift from cloud-only to cloud-optional is subtle and will not be obvious to end users, it really is a fundamental paradigm shift. This move provides a number of business opportunities for increasing revenue and efficiencies and helps ensure sustained service for customers.

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How 5G is enhancing communication in critical sectors

Luke Wilkinson, MD, Mobile Tornado

In critical sectors where high-stakes situations are common, effective communication is non-negotiable. Whether it’s first responders dealing with a crisis or a construction team coordinating a complex project, the ability to share information quickly and reliably can mean the difference between success and failure.

Long-distance communication became feasible in the 1950s when wireless network connectivity was first utilised in mobile radio-telephone systems, often using push-to-talk (PTT) technology. As private companies invested in cellular infrastructure, the networks developed and data speeds improved increasingly. Each major leap forward in mobile network capabilities was classed as a different generation and thus 1G, 2G, 3G, 4G, and now 5G were born.

5G is the fifth generation of wireless technology and has been gradually rolled out since 2019 when the first commercial 5G network was launched. Since then, the deployment of 5G infrastructure has been steadily increasing, with more and more countries and regions around the world adopting this cutting-edge technology.

Its rollout has been particularly significant for critical sectors that rely heavily on push-to-talk over cellular (PTToC) solutions. With 5G, PTToC communications can be carried out with higher bandwidth and speed, resulting in clearer and more seamless conversations, helping to mitigate risks in difficult scenarios within critical sectors.

How is 5G benefiting businesses?

According to Statista, by 2030, half of all connections worldwide are predicted to use 5G technology, increasing from one-tenth in 2022. This showcases the rapid pace at which 5G is becoming the standard in global communication infrastructure.

But what does this mean for businesses? Two of the key improvements under 5G are improved bandwidth and download speeds, facilitating faster and more reliable communication within teams. PTToC solutions can harness the capabilities of 5G and bring the benefits to critical sectors that need it most, whether that’s in public safety, security, or logistics: the use cases are infinite. For example, this could be leveraging 5G’s increased bandwidth to enable larger group calls and screen sharing for effective communication.

Communication between workers in critical industries can be difficult, as often the workforces are made up of lone workers or small groups of individuals in remote locations. PTToC is indispensable in these scenarios for producing quick and secure communication, as well as additional features including real-time location information and the ability to send SOS alerts. PTToC with 5G works effectively in critical sectors, as 5G is designed to be compatible with various network conditions, including 2G and 3G. This ensures that communication remains reliable and efficient even in countries or areas where 5G infrastructure is not fully deployed to keep remote, lone workers safe and secure.

The impact of 5G on critical communications

The International Telecommunication Union has reported that 95 percent of the world’s population can access a mobile broadband network. This opens up a world of new possibilities for PTToC, particularly when harnessing new capabilities for 5G as it’s being rolled out.

One of the most significant improvements brought by 5G is within video communications, which most PTToC solutions now offer. Faster speeds, higher bandwidth, and lower latency enhance the stability and quality of video calls, which are crucial in critical sectors. After all, in industries like public safety, construction, and logistics, the importance of visual information for effective decision-making and situational awareness cannot be overstated. 5G enables the real-time transmission of high-quality video, allowing for effective coordination and response strategies, ultimately improving operational outcomes and safety measures.

Challenges in Adopting 5G in Critical Sectors

While the benefits of 5G are undeniable, the industry faces some challenges in its widespread adoption. Network coverage and interoperability are two key concerns that need to be addressed to ensure communication can keep improving in critical sectors.

According to the International Telecommunication Union, older-generation networks are being phased out in many countries to allow for collaborative 5G standards development across industries. Yet, particularly in lower-income countries in Sub-Saharan Africa, Latin America, and Asia-Pacific, there is a need for infrastructure upgrades and investment to support 5G connectivity. The potential barriers to adoption, including device accessibility, the expense of deploying the new networks, and regulatory issues, must be carefully navigated to help countries make the most out of 5G capabilities within critical sectors and beyond.

However, the rollout of 5G does cause data security concerns for mission-critical communications and operations, as mobile networks present an expanded attack surface. Nonetheless, IT professionals, including PTToC developers, have the means to safeguard remote and lone workers and shield corporate and employee data. Encryption, authentication, remote access, and offline functionality are vital attributes that tackle emerging data threats both on devices and during transmission. Deploying this multi-tiered strategy alongside regular updates substantially diminishes the vulnerabilities associated with exploiting 5G mobile networks and devices within critical sectors.

While the challenges faced by the industry must be addressed, the potential benefits of 5G in enhancing communication and collaboration are undeniable. As the rollout of 5G continues to gain momentum, the benefits of this cutting-edge technology in enhancing communication in critical sectors are becoming increasingly evident. The faster, more reliable, and efficient communication enabled by 5G is crucial for industries that rely on real-time information exchange and decision-making.

Looking ahead, the potential for further advancements and increased adoption of 5G in critical sectors is truly exciting. As the industry continues to address the challenges faced, such as network coverage, interoperability, and data security concerns, we can expect to see even greater integration of this technology across a wide range of mission-critical applications for critical sectors.

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