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Thank you, Enterprisers!

admin — Mon, 15 May 2023 07:00:00 +0000

Thank you, Enterprisers! admin May 15, 2023 - 3:00am

Over the years, we have had the honor of sharing your knowledge, insights, and ideas with readers through this publication. It has been a wonderful journey—nearly ten years in the making.

We must share the news that The Enterprisers Project's funding has come to an end. What that means for the future is not yet clear. Publication of new articles must end, although the site will remain online indefinitely.

The Enterprisers Project has always been a space where IT leaders and executives could learn from each other. It has been a pleasure to be a part of this vibrant community, and we are proud of what we have built together.

As we part ways, we want to take a moment to thank you all for your contributions, support, feedback, and engagement. Your passion and dedication to innovation, leadership, technology, and how it all fits together has been an inspiration to us. We are confident that the conversations and relationships we have built here will continue to thrive and grow.

Keeping up with Red Hat

Red Hat funded The Enterprisers Project for nearly a decade. You can keep up with Red Hat here.

After nearly 10 years, this community-powered publication for IT leaders is ending.

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Automation: 3 ways it boosts productivity and reduces burnout

Aytekin Tank — Thu, 11 May 2023 07:00:00 +0000

Automation: 3 ways it boosts productivity and reduces burnout Aytekin Tank May 11, 2023 - 3:00am

Reports of mass layoffs are all over the headlines these days. As of April 2023, job cuts rose to 270,416—an increase of 396% from the same period a year ago. The tech sector, in particular, has taken a bruising, with 102,391 jobs slashed this year so far, an increase of 38,487%.

The other side of the coin, which doesn’t always make the headlines, is the employees who manage to hold onto their positions. In addition to simmering anxiety about their careers, these employees have to grapple with significantly larger workloads. In the tech industry, for example, one report found that the number of weekend hours jumped to 11.5 hours on average—a 31 % increase.

As CEO of Jotform, I understand the stress of these turbulent times. But I’m also a fervent advocate for the power of rest. The only way to bridge these two realities is to increase productivity through automation. Using automated tools and systems, employees can get more done when they’re “on,” and fully disconnect when they’re “off.”

[ Also read IT leadership: How to focus your automation strategy. ]

Here’s a closer look at how automation serves both your employees' and your company’s well-being.

1. Automation boosts productivity

In my new book, I write at length about the perils of busywork—manual, rote, repetitive tasks that, while necessary, don’t supercharge motivation or leave us feeling fulfilled. We all have our own version of busywork, be it invoicing, scheduling, emailing, or any other activity that we tend to complete on overdrive.

The truth is, doing things manually takes time, especially when you consider the various human pitfalls like distraction, boredom, and sheer forgetfulness. We’ve all been there—you decide to reply to a few quick emails before turning to a cognitively demanding task, and suddenly an hour disappears and you’re too mentally fatigued to tackle your more important work.

With automation tools—for example, automatically filing emails, saving spreadsheets, or organizing a meeting calendar—tasks that normally take minutes (or hours) are reliably completed in seconds or even milliseconds. We’re left with more uninterrupted time to take care of the big stuff.

Identify your version of busywork, break it down into steps, and find the best tools out there to take care of the rote, repetitive parts of the sequence.

2. The more automation, the more engagement

Busywork isn’t just a productivity killer. When it chips into our time for the big stuff, it destroys engagement too. And with the current economic turmoil leaving employees fearful for their jobs, engagement is both more precarious and precious than ever.

When we automate, we can carve out more time for the big stuff—and the more time we spend on the big stuff, the more engaged we become.

When we automate, we can carve out more time for the big stuff—and the more time we spend on the big stuff, the more engaged we become. Engaged employees aren’t just happier; they also create better customer experiences. Companies, in turn, can charge more for their services.

The bottom line: Higher engagement is a win for everyone—companies, customers, and employees alike.

To identify your most meaningful work, ask yourself what you enjoy doing the most and what delivers the most impact. For me, that’s writing and high-level strategizing. For a journalist, it might be drafting compelling narratives. For a designer, it might be brainstorming creative and beautiful ways to solve a customer’s problem.

As you work toward automating as many steps as possible, keep this “meaningful work” vision in mind. It will be a compass on your automation journey.

3. Top-down automation strengthens your business

The benefits of automation are multifold: It increases engagement and productivity; it overcomes human limitations like the need to rest because with automation you set it and forget it; it minimizes errors; and it establishes processes that can be consistently refined. This list is not exhaustive.

But here’s the rub: Automation can’t be established in a vacuum. A single employee can’t create a work environment that promotes automation. In order to truly harness the power of automation, automation strategies and their associated protocols must come from the top down.

Consider the practice of blocking out time for deep work. When we automate, we can carve out these important time swaths and set our status to unavailable. But one employee can’t go off the radar without the cooperation of her colleagues. To successfully establish this kind of workplace norm, there must be mutual understanding and support from management.

As leaders, we can encourage employees to automate and to fully take advantage of the benefits that flow from automation. That way, everyone is on the same page.

When everyone in the company is giving themselves space to do their most meaningful work, balanced with ample time for rest, it creates a virtuous cycle. The work becomes its own reward—and might even feel lighter than ever.

[ How can automation free up more staff time for innovation? Get the free eBook: Managing IT with Automation. ]

Layoffs are impacting all employees—even those left behind, who often suffer surging burnout. Here’s how automation can help.

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Automation

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Large language models: 6 pitfalls to avoid

Eoin Wickens — Thu, 04 May 2023 07:00:00 +0000

Large language models: 6 pitfalls to avoid Eoin Wickens May 4, 2023 - 3:00am

There has recently been incredible progress in artificial intelligence (AI), due mainly to the advances in developing large language models (LLMs). These are the beating heart of text and code generation tools such as ChatGPT, Bard, and GitHub’s Copilot.

These models are on course for adoption across all sectors. But serious concerns remain about how they are created and used—and how they can be abused. Some countries have decided to take a radical approach and temporarily ban specific LLMs until proper regulations are in place.

Let’s look at some real-world adverse implications of LLM-based tools and some strategies to mitigate them.

1. Malicious content

LLMs can improve productivity in many ways. Their ability to interpret our requests and solve fairly complex problems means we can offload mundane, time-consuming tasks to our favorite chatbot and simply sanity-check the results.

But of course, with great power comes great responsibility. While LLMs can create helpful material and speed up software development, they can also enable rapid access to harmful information, accelerate the workflow of the bad guys, and even generate malicious content such as phishing emails and malware. The term “script kiddie” takes on a whole new meaning when the barrier to entry is as low as writing a well-constructed chatbot prompt.

While there are ways to restrict access to objectively dangerous content, they’re not always feasible or effective. In terms of hosted services like chatbots, content filtering can help to at least slow down an inexperienced user. Implementing strong content filters should be imperative, but they’re not bulletproof.

[ Also read Generative AI: 3 do's and don'ts for IT leaders. ]

2. Prompt injection

Specially crafted prompts can coerce an LLM into ignoring content filters and producing illicit output. This issue pervades all LLMs but is about to be amplified as these models connect with the outside world; for example, as plugins for ChatGPT. These could enable chatbots to ‘eval’ user-generated code, which can lead to arbitrary code execution. From a security perspective, equipping a chatbot with such functionality is very problematic.

To help mitigate this, it’s important that you understand the capabilities of your LLM-based solution and how it interacts with external endpoints. Determine if it has been connected to an API, is running a social media account, or is interacting with your customers without supervision, and evaluate your thread model accordingly.

While prompt injection may have appeared inconsequential in the past, these attacks can have very real consequences now as they begin to execute generated code, integrate into external APIs, and even read your browser tabs.

3. Data privacy/Copyright violation

Training large language models requires tremendous amounts of data, with some models numbering over half a trillion parameters. At this scale, understanding provenance, authorship, and copyright status is a gargantuan—if not impossible—task. An unvetted training set can result in a model that is leaking private data, misattributing citations, or plagiarizing copyrighted content.

Data privacy laws around the usage of LLMs are also very murky. As we’ve learned with social media, if something is free, chances are that users are the product. It’s worth remembering that if we ask a chatbot to find the bug in our code or to write a sensitive document, we’re sending that data to a third party, who may end up using it for model training, advertising, or competitive advantage. Data leakage through AI prompts can be especially damaging in business settings.

As LLM-based services become integrated with workplace productivity tools such as Slack and Teams, it’s crucial to carefully read providers’ privacy policies, understand how the AI prompts can be used, and regulate the use of LLMs at the workplace accordingly. Regarding copyright protections, we need to regulate data acquisition and use through opt-ins or special licensing without hindering the open and largely free internet as we have it today.

4. Misinformation

While they can convincingly feign intelligence, LLMs don’t really “understand” what they produce. Instead, their currency is the probabilistic relationships between words. They can’t distinguish between fact and fiction—some output might appear very believable but turn out to be a confidently worded untruth. An example of this is ChatGPT falsifying citations and even entire papers, as one Twitter user recently discovered first-hand.

LLM tools can prove incredibly useful in a vast array of tasks, but human beings must be involved in verifying the accuracy, benefits, and overall sanity of their responses.

The output of LLM tools should always be taken with a pinch of salt. These tools can prove incredibly useful in a vast array of tasks, but human beings must be involved in verifying the accuracy, benefits, and overall sanity of their responses. Otherwise, we are in for some disappointment.

5. Harmful advice

When chatting online, it’s becoming increasingly difficult to tell if you’re speaking to a human or a machine, and some entities might be tempted to take advantage of this. Earlier this year, for example, a mental health tech company admitted that some of its users who sought online counseling were unknowingly interacting with a GPT3-based bot instead of a human volunteer. This raised ethical concerns about using LLMs in mental healthcare and any other setting that relies on interpreting human emotions.

Currently, there’s little to no regulatory oversight in place to ensure that companies cannot utilize AI in this manner with or without the end user’s explicit consent. Moreover, adversaries can use convincing AI bots in espionage, scams, and other illegal activities.

AI doesn’t have emotions, but its responses can hurt people’s feelings or even lead to more tragic consequences. It’s irresponsible to assume that an AI solution can adequately interpret and respond to the emotional needs of a person responsibly and safely.

The use of LLMs in healthcare and other sensitive applications should be closely regulated to prevent any risk of harm to users. Providers of LLM-based services should always inform users of the scope of AI’s contribution to the service, and interacting with a bot should always be a choice rather than the default.

6. Bias

AI solutions are only as good as the data they’re trained on. This data often reflects our human biases toward political parties, ethnic groups, genders, or other demographics. Bias brings about negative consequences for the affected groups, where the model makes an unfair decision and can be both subtle and potentially difficult to address. Models trained on unvetted data from the Internet will always mirror human biases; models that constantly learn from user interaction are also prone to intentional manipulation.

To mitigate the risk of discrimination, LLM service providers must carefully evaluate their training datasets for any imbalances that may result in negative consequences. Machine learning models should also be periodically checked to ensure the predictions remain fair and accurate.

Large language models are completely redefining how we interact with software, bringing countless improvements to our workflows. However, with the current lack of meaningful regulations around AI and the scarcity of security aimed at machine learning models, the widespread and hasty implementation of LLMs will likely have significant downfalls. It’s therefore imperative to swiftly regulate and secure this precious technology.

[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]

From security and privacy concerns to misinformation and bias, large language models bring risk along with rewards.

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Marta Janus

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Why generative AI won't solve your cloud spending woes

Willy Sennott — Thu, 04 May 2023 07:00:00 +0000

Why generative AI won't solve your cloud spending woes Willy Sennott May 4, 2023 - 3:00am

In case you somehow missed it, the generative AI revolution is upon us. Tools like ChatGPT are famously capable of producing everything from computer code to poetry, with impressive accuracy and sophistication.

But here’s one thing that generative AI is not capable of doing, at least not anytime soon: Helping to solve cloud spending woes. It would be nice if figuring out how to cost-optimize your cloud were as simple as asking an AI engine for tips, but that’s not happening—not because generative AI technologies aren’t impressive (they are) but because AI tools currently lack the ability to understand feedback loops and nuanced business context.

To prove the point, let’s look at what AI can do in the context of cloud cost optimization, then detail why it remains incapable of helping businesses conquer cloud spending challenges.

The long history of AI and cloud cost optimization

Although it has only been in the past half-year or so that generative AI began making flashy headlines, the cloud cost optimization ecosystem has been leveraging AI in other forms for quite a long time.

The fundamental process at the heart of most cloud cost optimization tools is predictive analytics, which is a form of AI and machine learning. For cost management purposes, predictive analytics involves deploying algorithms that assess cloud spending and workload performance data.

[ Also read Generative AI: 3 do’s and don’ts for AI leaders. ]

Those algorithms are trained to predict spending patterns. Cost optimization tools can also parse historical spending data to identify anomalies associated with overspending. They then surface the mistakes to help businesses save money in the cloud. This is how tools like AWS Compute Optimizer have worked for years.

To be sure, generative AI tools do more than just predictive analytics and anomaly detection, and they are trained on data sets much larger than those used by your standard cloud cost optimization tools. Still, at the end of the day, both categories of tools—generative AI technologies and traditional cloud cost optimizers—deliver insights in the same fundamental way, by parsing data sets using machine learning models. There’s nothing remarkably new in this respect about generative AI tools as compared to the cloud cost optimizers that have been delivering insights via predictive analytics for years.

The limitations of AI for reducing cloud spending

Given that the application of AI-powered technology to cloud cost optimization is hardly new, it’s hard to imagine the latest breed of AI tools faring any better than traditional solutions when it comes to helping businesses to reduce cloud spending.

The main reason why is that next-generation AI tools, as well as traditional cloud cost optimization software, are subject to some major limitations in their ability to understand cloud spending patterns and needs. The most important is that they can’t incorporate customer feedback in order to refine their recommendations over time. Instead, they provide generic, crude recommendations that might be in the interests of the typical business but that may or may not make sense for your particular company or for the workload it operates.

In other words, generative AI, like conventional cloud cost management tools, offers users no way of saying, “I’m not going to accept your recommendation to move this workload to a different EC2 instance because doing so would violate my business’s governance rules. Please make a new recommendation.”

You can’t explain critical context to AI tools and expect them to respond effectively.

Nor can you say, “I took the recommendation you gave me last month to modify the hosting configuration for a little-used application, but today our CMO announced that we’ll be promoting that application heavily and we expect traffic to pick up significantly. How should we update the configuration to reflect the changing business context of the app?”

You can’t explain critical context like this to AI tools and expect them to respond effectively.

Relatedly, AI tools often need human guidance to achieve their goals. For example, although an AI tool could parse workload configuration data and analyze performance and spending metrics, it likely can’t tell the difference between a testing workload and production workload unless you tell it how to determine the difference (by, for example, looking at workload tags). Nor can it understand how the needs of different business units, different groups or customers, varying budgetary priorities and so on impact cloud spending unless, again, you provide guidance.

The only way to work around these limitations of AI in the context of cloud cost management is to bring humans into the fold. You need humans who understand the nuances of cloud spending and who can identify and assess cloud savings recommendations based on the unique context of every workload and every business.

The future of AI and cloud cost management

It’s worth pointing out that there are ways that modern AI technology could evolve to address the shortcomings I’ve highlighted, at least in theory. Conceptually, it might be possible for the algorithms behind a tool like ChatGPT to accept human feedback about what works and what doesn’t with regard to cloud spending initiatives, then use the feedback to refine recommendations over time. It is also theoretically feasible for these tools to collect and analyze data, such as email streams, which give them insight into business context.

But currently, no generative AI tool is designed to do these things. And even if such tools did exist, there will always be some amount of business context and nuance that AI tools can’t learn by simply ingesting data. There will also always be some level of unknowability about a business’s cloud workload requirements,

So, while AI might evolve over time and become somewhat better at helping to manage cloud costs, it’s virtually impossible to imagine a world where AI alone gets you more than perhaps 50% of the way toward optimizing cloud spending.

Human oversight still required

There are many ways in which generative AI tools could potentially help to smooth over some of the rougher edges of cloud cost optimization. For example, finance teams could use natural language models to interpret jargon-heavy technical descriptions from engineers about what cloud workloads require. Or businesses could use AI tools to explain pricing structures for complicated cloud workloads in a way that humans can more easily understand. AI tools can also play a key role in bringing both technical and non-technical stakeholders up to speed quickly on a wide variety of topics, including helping to explain and support cost optimization recommendations.

That said, there is simply too much nuance and complexity in the discipline of cloud cost optimization ecosystem for AI tools to automate away cost management tasks entirely. They just can’t refine their recommendations well enough in a context-aware way to deliver actionable results without requiring humans to participate in the process or, at a minimum, provide critical guidance.

If they could, you’d expect that there would be AI tools out there that can optimize cloud costs just as well as they can write code or poetry. But there aren’t, and it’s hard to imagine there ever will be, because cloud cost management is just not as simple or repeatable as the types of tasks that AI can handle more effectively without human assistance.

[ Want best practices for AI workloads? Get the eBook: Top considerations for building a production-ready AI/ML environment. ]

Generative AI tools have plenty of potential business use cases. Here's why optimizing your organization's cloud costs isn't among them.

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7 ways to improve employee experience and workplace culture

Chris Priebe — Wed, 03 May 2023 07:00:00 +0000

7 ways to improve employee experience and workplace culture Chris Priebe May 3, 2023 - 3:00am

Engaged employees are more productive and less likely to quit. But creating engagement is easier said than done. A recent study by Gartner found that only 13% of employees feel completely satisfied with their experience at work.

While HR initiatives like active listening and career progression are important for the mid- to long-term employee journey, IT plays an important role from day one to ensure that all employees have the tools and resources they need to be productive. IT teams and HR must work together to create an organizational culture in which employees can thrive.

Here are 6 things business and IT leaders can do to improve workplace culture.

1. Provide proper equipment

Equipment is fundamental for all businesses. A functioning workplace needs the right equipment for employees to achieve their objectives. As technology evolves and becomes more prevalent in all aspects of a business, it’s increasingly important to make informed decisions for better operational management.

We are contending with a post-pandemic world in which remote work is more accepted, resulting in an increased need for control over employee devices.

With hybrid setups, we’re seeing the security and logistical challenges that come from ensuring employees have the tools they need. Consider the acquisition of equipment, which can be difficult thanks to import duties that make international shipping more challenging.

[ Also read Reimagining employee retention: 4 tips. ]

On top of that, employees have personal preferences. Some people work more productively on a Mac and others on a Windows computer. Corporate policies should not force employees into making choices that impede their own productivity.

2. Offer the best tools

In today’s remote and hybrid workplace, communication has become more difficult, particularly for companies with a large percentage of remote employees. But effective communication is essential for any business to succeed, and it has always been a cornerstone of successful operations.

Inadequate communication can lead to fragmented, unfinished, and inconsistent work from teams and collaborators. In addition to impacting the quality of work, poor communication can also harm company culture and hinder employees’ professional growth of employees.

Recognize that practices and tools that were considered state-of-the-art just a few years ago may no longer be effective or efficient. Employees prefer tools that offer consumer-grade user experiences, lighting-fast page loads powered by sophisticated caching, and easy access across web, mobile, and chatbots.

Practices and tools that were considered state-of-the-art just a few years ago may no longer be effective or efficient.

3. Promote freedom

The shift to remote work has given employees more flexibility and control over their work-life balance. Consider enabling your employees with options such as reduced working hours, flexible work locations, time off, and increased opportunities for learning and development.

Rather than asking, “Why should this be allowed?” ask the opposite. Unless there is a good reason not to do so, don’t be afraid to give employees new freedoms.

This comes with new challenges, and managing hybrid and remote work arrangements can be challenging. One critical aspect is to ensure that remote employees can securely and seamlessly access company systems wherever they are located.

4. Provide fast, reliable internet

Access to high-quality internet is crucial for both businesses and employees. The most effective productivity tools require fast and responsive internet connections, with split-second page load times. A slow or laggy internet connection can significantly disrupt work, hinder productivity, and cause frustration.

If you have employees working from home, consider supplementing their home internet plan upgrades. A study conducted by ComputerWeekly found that employees working from home lose over half an hour of work per day, on average, due to internet problems. This means the ones with particularly unreliable internet may lose more than an hour daily.

If you’re in an office environment, investing in fast and reliable internet ensures these disruptions don’t occur and can help motivate employees to work from the office more often.

5. Meet employees eye-to-eye

The traditional hierarchical way of managing employees has been shown to be largely ineffective. Companies run as adhocracies are more productive as they foster knowledge sharing, workplace collaboration, and rapid adaptation—some of the most important attributes for companies in the knowledge-based age.

By encouraging employees to be more self-sufficient and less dependent on their superiors, you can promote greater efficiency and effectiveness in the workplace.

Start adopting more self-service options for employees. Modern IT and HR systems can be calibrated to your employees’ needs and enable them to help themselves, whether they want to book a vacation, access important documents, get a better screen, or access an enterprise app.

6. Have an amazing office

Although hybrid and remote work seems to be the preferred model for many organizations, it still has disadvantages.

Many remote and hybrid employees struggle to manage the blurred boundary between work and personal life, or the often less-than-ideal workplace setups.

Having access to an amazing office has become an employee perk. Modern offices should incorporate innovative ideas that enhance employees’ workplace comfort and productivity. There is a clear ROI to invest in a high-quality office environment that compensates for the additional time and money employees spend on commuting.

It’s time to abandon the old-fashioned workplace environment of small cubicles and narrow glass dividers. Instead, strive to create an open, airy environment with plenty of natural light, spacious workstations, professional desks and chairs, high-quality equipment, comfortable seating, and greenery to add liveliness to the workplace.

7. Schedule offsites

Agile: 4 key business boosts

Scott Opitz — Mon, 01 May 2023 07:00:00 +0000

Agile: 4 key business boosts Scott Opitz May 1, 2023 - 3:00am

As innovation continues to help organizations enhance their operations and improve efficiency, consumers’ expectations of the experience and value they receive will evolve. Speed of service remains a top priority, and consumers no longer need to waste time with businesses that can’t meet their needs.

This poses a significant problem for businesses that have clung to legacy platforms or failed to digitally transform their internal processes. The decentralization of technology, the rise of intelligent automation, and the increasing importance of the customer have enabled businesses on the bleeding edge to quickly adapt and deliver value at the speed of thought.

This is achieved through agile processes—processes that are both quick and easily responsive to change or external factors. By pursuing agility, organizations can eliminate unnecessary red tape within their operations and deliver a more satisfactory customer experience while also allowing employees to adjust their tools and workflows to their strengths and the reality of their work.

While “agility” might seem like a catch-all buzzword, it is an achievable outcome when implemented with the right tools and platforms and with efficiency in mind. From increasing revenue to customer loyalty, read on for 4 ways agile processes can improve organizations.

1. Low-code/no-code empowers citizen developers/business users

Employees’ productivity can be limited by the tools that they use. Not all processes look the same end-to-end, and unexpected variables or unique scenarios can require customization of tools and platforms.

[ Also read Agile transformation: 3 obstacles and how to overcome them. ]

If these tools can’t be adapted without extensive IT knowledge, a once-simple task then requires help desk tickets, email correspondence, and more overall obstacles than if the initial user is able to make the necessary changes themselves.

This is where low-code/no-code platforms enable agile organizations to expedite internal processes and elevate employees to citizen developers. Intuitive, accessible, and customizable tools can ease tasks and prevent technical debt. Organizations can adjust to client needs on an ad-hoc basis without unnecessary bureaucracy.

Tax season, for example, brings an influx of highly detailed forms with a wide range of personal information and special circumstances. A rigid platform for document processing would severely limit the processing of a business or individual’s finances. Tax services with legacy platforms that require advanced coding to modify would yield significantly slower processing times than a counterpart using low-code/no-code tools.

By improving straight-through processing rates of documents and reducing the need for human intervention, low-code/no-code document processing allows for agile adaptation that will help organizations provide speedy and satisfying service to customers.

2. Agile front-end processes improve customer experience and retention

Slow customer onboarding and other tedious front-facing processes will discourage use of your product or service.

Arduous identity verification and repetitive manual entry are the antithesis of agility and will not garner customer loyalty when, for example, banking institutions have set a standard for an almost instantaneous speed of service.

A recent survey identified organizations’ top reasons for abandonment during customer onboarding, among which were excessive steps (29%), difficult identity proofing (26%), and excessive manual entry (26%), among others.

Proof of identity is a key pain point that can drastically improve the agility of the onboarding process, reducing dropout rates and improving customer loyalty and advocacy. Requiring users to toggle between various screens, email documents to themselves, or dig up personal information presents too many obstacles and opportunities for customers to get distracted and abandon the process.

Limiting proof of identity to just a few steps that can be completed from a single application or interface keeps users engaged and satisfied, reflecting a professional organization that values its customers’ time.

3. Intelligent processes increase revenue

Agile processes that directly relate to revenue, such as accounts payable, can increase profitability.

Invoice processing is inherently document-heavy and can involve laborious and repetitive manual entry if organizations haven’t automated it. Opting for manual entry over automation solutions wastes time and money and increases the likelihood of errors.

Agile accounts payable processes enable a higher, faster volume of processing with fewer errors, allowing businesses to take advantage of early payment discounts, avoid duplicate payments, and decrease cost per invoice.

4. AI tools improve business logic and processes

Agility remains a priority

Agility is not a fad driven by recent trends in artificial intelligence and machine learning. It’s an approach to operations that brings objective improvements in sustainability and improves employee and customer experiences. Although many organizations have not reached full maturity with agile processes, innovation in automation and the use of other intelligent solutions suggest that returns on investment in agility are only going to grow.

[ Learn how leaders are embracing enterprise-wide IT automation: Taking the lead on IT Automation. ]

Agile processes are fast becoming imperative to keep up with today’s business demands. Here are 4 practical examples of how agility can benefit your organization.

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The future of healthcare is in the cloud

Sam Johnson — Thu, 27 Apr 2023 07:00:00 +0000

The future of healthcare is in the cloud Sam Johnson April 27, 2023 - 3:00am

Across life sciences and health care (LSHC), cloud adoption is rising as organizations accelerate their business and digital transformation efforts.

Some seek the traditional benefits that the cloud offers – scalability, flexibility, the ability to optimize costs, and access to the latest technology. However, many organizations have realized that the bigger potential of the cloud may lie in creating seamless consumer-centric experiences for patients and customers and in building workflows that drive better outcomes while fostering greater collaboration.

What’s in the cloud for LSHC organizations?

Although each LSHC organization has its own goals for the cloud, key workloads across the LSHC sector are commonly being moved there. Typically, moving these workloads can help improve operational efficiency and optimize IT costs, which can ultimately help enhance the patient experience. They include:

Electronic health records (EHRs): EHRs are used for managing patient data. Moving them to the cloud can help providers centralize data and allow real-time access.

Medical imaging: Moving storage-intense imaging workflows such as X-rays and CT scans to the cloud can offer a cost-effective storage option and improve accessibility.

Telemedicine: Cloud-based solutions can provide secure video conferencing and other tools to facilitate improved workflows and remote consultations with patients.

Patient monitoring: Cloud-based patient monitoring can provide real-time data and enable remote monitoring of patients in their homes. The cloud also can drive similar monitoring benefits for research and clinical trials.

Claims processing: Cloud-based claims processing can improve the accuracy and speed of claims processing, which can improve the overall efficiency of providers and organizations. Process automation can also help reduce administrative errors.

Revenue cycle management: Cloud-based revenue-cycle management can help providers manage billing and payments more effectively, which can improve cash flow and reduce administrative costs.

Fostering collaboration to enhance the patient experience

Migrating workloads to the cloud – in particular, utilizing tailored industry cloud solutions that address heart-of-the-business issues and foster the convergence of technology with industry-specific data and personalization to speed transformation – often leads to increased collaboration among business areas. This improved collaboration helps LSHC organizations identify internal challenges, build consensus for ambitious initiatives, and unlock additional value from shared resources and systems.

[ Also read 5 ways to optimize your journey to the cloud. ]

For example, chief medical officers, CFOs, CIOs, chief digital officers, chief procurement officers, and chief regulatory officers all increasingly find themselves in discussions that cover the cloud and the future of the patient experience. This reflects the fact that providing a seamless experience for patients requires cooperation from multiple business areas throughout the organization, which compels those areas to understand each other’s workflows.

However, after years of IT sprawl and operating in relative isolation, operational systems and departments are often siloed. The cloud can break down these silos because it provides universal access to information that can encourage collaboration and information-sharing and ultimately enhance the patient experience.

Overcoming the most pressing cloud challenges

Although most LSHC organizations recognize the potential value of the cloud, they’re also realistic enough to understand that significant cultural and technical challenges come with cloud adoption. The challenges are also often exacerbated by concerns about sunk costs in existing EHR systems and other on-premises solutions. These obstacles can be overcome with the right combination of planning, technology, and execution.

Security is paramount

Data security, resiliency, and privacy are critical issues. Healthcare providers need to ensure that patient data is protected and in compliance with regulatory requirements, which demands careful design and implementation of EHRs and other systems that contain patient data. It also requires constant monitoring to ensure security and compliance. Cloud solutions – whether hyperscaler platforms, data warehouses, or specific apps – must align with those needs.

To address this, providers should ensure that their cloud solutions are based on a framework of trust and resilience. They need a secure and compliant platform for managing patient data in the cloud that meets HIPAA and other regulatory requirements and that includes customizable features, and standard encryption, access controls, and audit logs.

The cloud environment must also be designed to support the digital resilience of systems that support critical business functions. In short, for providers to feel comfortable with scaling cloud systems, they need to find the right system for their unique needs, which likely means leaning on an industry-specific product or group of products.

Integration is pivotal

Integration is another crucial concern, and it’s pivotal for getting more value from cloud and existing investments in EHR systems as well as securing better outcomes for patients. By connecting and eventually migrating EHR solutions to the cloud, LSHC organizations can run new cloud-native tools alongside their EHR solution, which can enhance workflows with capabilities like new dashboards for deeper insights, AI for process automation and alerts, chatbots for customer service, and more.

However, leaders may worry that during cloud migration, some essential data and processes could fall through the cracks – or that they may create new silos as workloads move. As a result, they may want to keep some systems, such as their EHR system, on-premises, which could hamper the adoption of digital innovations as they emerge and delay the delivery of outcomes that patients need, and providers expect.

Unleashing the power of the cloud

The future of the cloud in health care continues to evolve. But we continue to see two constants that will remain in focus across the industry: elevating outcomes and increasing collaboration.

By keeping the emphasis on securing better patient outcomes, healthcare providers can help individuals live healthier and more productive lives. And they do something similar when they collaborate around the cloud – they help their own organizations become healthier and more productive through stronger internal communities working together to unleash the power of the cloud.

[ Build application environments for reliability, productivity, and change. Download the eBook, Cloud-native meets hybrid cloud: A strategy guide. ]

Here's how cloud technologies are overcoming challenges and reshaping possibilities for life sciences and healthcare

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Enterprise Technology

Cloud

Security

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Cloud computing: 3 business advantages

Vikas Gupta — Wed, 26 Apr 2023 07:00:00 +0000

Cloud computing: 3 business advantages Vikas Gupta April 26, 2023 - 3:00am

Most global enterprises have embraced – or at least considered – moving to cloud computing, and the momentum continues to grow. According to data from Gartner, worldwide end-user spending on public cloud services is forecast to reach $591.8 billion in 2023, up from $490.3 billion in 2022.

But for those who are slow to adopt the cloud, its benefits can seem unclear, especially given the significant effort required to move decades of data from on-prem servers. Regardless of the size of your organization, moving to the cloud is imperative if you want to be an innovator in the next decade.

The most successful cloud migrations happen when business leaders keep the problem they are trying to solve at the forefront. This ensures that cloud investments translate to business outcomes that will continue to push the business forward.

Here are three ways to leverage the cloud to benefit your business in 2023.

1. Choose the right cloud strategy

Before you can leverage the capabilities of the cloud, you must decide which hyperscaler or combination of hyperscalers (and/or private clouds) will best serve your business’s needs. Consider security, compliance, scalability, and ease of use – which of these to prioritize depends on the business problems you are trying to solve.

Look for options with a broad range of services, a strong track record of reliability, and features from storage and computing to machine learning and analytics. As a CIO, you want to make your team's transition as easy as possible. A hybrid cloud solution will allow your organization to connect its on-premises infrastructure with the cloud. This will enable a smoother transition that is largely undetectable by end customers.

[Also read 5 ways to optimize your journey to the cloud. ]

Evaluate the pros and cons of each provider and consider a multi-cloud strategy that allows you to use multiple public cloud vendors alongside private clouds. This approach will enable you to optimize for cost, use case, and flexibility, and to avoid vendor lock-in.

2. Increase speed to innovation

Once your business has settled on a hyperscaler, an immediate cloud-related advantage is its ability to expedite internal and external business processes.

Take retail, for example. Prior to the cloud, launching a new point-of-sale system took months of manual development and labor, along with trial and error. It was impossible to make changes without taking the system offline, resulting in potential revenue loss. Plus, these solutions were expensive to build and deploy.

Cloud platforms allow organizations to quickly spin up new infrastructure, services, and applications without significant downtime or capital investment. This means your organization can test new ideas and business models quickly and easily without worrying about the high costs associated with traditional IT infrastructure and platform revisions.

Further, major cloud providers often offer built-in tools and services that accelerate innovation. Cloud-based machine learning tools can help your organization quickly develop and deploy new intelligent applications, like a 24-7 customer service chatbot, while cloud-based development environments can streamline the application development process.

3. Improve the customer experience

GPT-4: 5 ways it can help your digital transformation

Tristan Ovington — Tue, 25 Apr 2023 07:00:00 +0000

GPT-4: 5 ways it can help your digital transformation Tristan Ovington April 25, 2023 - 3:00am

While artificial intelligence (AI) has been gaining momentum for the past few decades, large language models (LLMs) like GPT-4 have created an explosion of interest from users wondering how they can support digital transformation. As a result of this popularity, Reuters predicts that the ChatGPT deep learning stack, upon which GPT-4 was based, will generate an income of USD $1 billion by 2024.

The popularity of GPT-4 is due to the power of AI technology, along with high user accessibility and broad versatility. Many different fields in the tech industry can utilize GPT-4 to automate and personalize many tasks, allowing staff to concentrate on more complex tasks.

Here are some examples of how GPT-4 can contribute to digital transformation in several different areas.

[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]

1. Personalized employee training

Generative AI like GPT-4 is an incredibly useful tool not only in business but also in training. Team leaders and HR professionals can use these programs to create creative and unique training programs that meet every employee’s learning needs, including accommodating different language and neurodivergence preferences. In these ways, GPT-4 is essential to help companies maintain momentum when introducing new digital tools as part of a transformation project.

In 2022, the educational organization Khan Academy began to introduce GPT-4 features to power its innovative AI assistant, Khanmigo. This AI assistant allows learners to learn autonomously and creatively in a personalized way, as they receive customized prompts for learning tasks. Khanmigo is a helpful use case for any organization training staff to use new technologies in their digital transformation.

2. Recruiting and marketing

Generative AI tools like GPT-4 could be a game-changer for marketing and advertising teams, which can tap their power to develop fresh, creative campaign ideas. And for those in recruitment and talent acquisition, tools like GPT-4 can help craft engaging content that persuades potential candidates to apply.

While these tools may never completely replace traditional professionals in marketing or advertising roles, they are useful for stimulating ideas during brainstorming sessions.

[ Also read Generative AI: How does it affect the enterprise? ]

3. Chatbots

Chatbots and digital assistants have become the talk of many industries, particularly tech and finance. As a result of this widespread use, Statista predicts the chatbot market to reach around USD $1.25 billion by 2025.

Leveraging GPT-4 technology, Morgan Stanley’s internal chatbot can now search through its vast PDF archives for answers to queries from its advisers. This is just one example of how a leading financial services corporation has begun exploring new ways to maximize its intellectual resources through the power of the LLM.

4. Security

As the internet evolves, so do the security risks associated with it. Predictably, GPT-4 provides problems as well as solutions. Malicious users have already used GPT-4 to conduct powerful enterprise attacks.

However, this tool serves as both cancer and cure: GPT-4 can be trained to assess potential attacks while deploying powerful protective measures and using deep learning from past threats to protect systems. Utilizing tools like these can address the security concerns of a digital transformation by ensuring that your personal information remains safe and secure online.

5. Accessibility

Through the power of GPT-4, the Danish business Be My Eyes has created a “virtual volunteer” to aid people with low vision or visual impairments lead more independent lives. This innovative technology offers assistance for daily activities and enables users to experience more freedom.

This GPT-4 feature could be used to help visually impaired staff members learn new digital tools during a digital transformation.

What’s next in the ChatGPT digital transformation journey?

Due to the success of previous ChatGPT models, GPT-5 will likely soon be on the horizon. It is expected to bring ever more powerful, accessible, and versatile features that can help organizations streamline their digital transformations.

Google’s Bard, Dall-E 2, and other competitors are also hot on the heels of OpenAI’s GPT offerings. As an IT leader, you should start researching the best LLM tools to catalyze your digital transformation.

GPT-4 can significantly boost your digital transformation’s potential when it’s used thoughtfully. Rather than investing heavily in IT infrastructure, focus on human feedback from staff members to create supportive environments for digital content producers.

When AI tools are introduced with solid collaboration between the C-suite and teams and are focused on employee engagement, they can be optimized for the best ROI. When this is achieved, your organization will make staff well-being a key part of a successful, lasting GPT-4 digital transformation.

[ Learn the non-negotiable skills, technologies, and processes CIOs are leaning on to build resilience and agility in this HBR Analytic Services report: Pillars of resilient digital transformation: How CIOs are driving organizational agility. ]

GPT-4 and other large language models are gaining momentum across industries. Check out these real-world examples of how these tools can boost your digital transformation.

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Enterprise Technology

Artificial Intelligence

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4 ways CIOs are rethinking digital transformation

Adam Glaser — Tue, 25 Apr 2023 07:00:00 +0000

4 ways CIOs are rethinking digital transformation Adam Glaser April 25, 2023 - 3:00am

Digital transformation (DX) is all about evolving an organization to new levels of agility, control, and value with its data and operations. As organizations learn to better strategize and implement their modernization initiatives, DX methodologies will continue to evolve.

Rethinking 4 key DX focus areas

The field of digital transformation—the tools, tactics, systems, and architectures that govern the modernization effort—is itself undergoing a transformation, enabling new approaches in artificial intelligence (AI), machine learning (ML), DevSecOps, automation, low-code, and other advances.

As game-changing capabilities and pioneering use cases pile up in the DX marketplace, here are 4 ways this evolution is prompting CIOs to rethink what’s possible.

1. Crafting automation strategy with a scalpel

It’s increasingly possible to fine-tune automation strategy. Whether it’s robotic process automation (RPA), AI, or other forms of automation, knowing which tool makes sense in which scenario is key. And this extends to fine-tuning the human component, tailoring exactly where and how people interact with automation tools for troubleshooting and decision support.

[ Also read How artificial intelligence can inform decision-making. ]

2. Low-code is solving the 'build-vs.-buy' conundrum

Intuitive low-code tools can eliminate that false choice between speed (buy) and flexibility (build) by empowering those closest to the business to map out the processes and delegate tasks to developers. And low-code doesn’t come with the capability tradeoffs of simplistic no-code tools. Developer productivity soars and businesses end up with highly bespoke software that meets their unique needs up to 10x faster than using traditional developer tools.

3. Enterprise-grade security can support both scale and velocity

Security and velocity don’t need to be mutually exclusive. By using modern platforms, digital transformation projects can materially enhance enterprise security while delivering business value at the same time. The key is ensuring core technologies support a DevSecOps approach to baking security into the development process combined with continuous improvement loops to iterate on security as the organization scales.

4. Architecting for the total experience

Orchestrating DX across the total experience means orchestrating modernization steps across legacy and cloud applications and a diverse array of endpoints, from smartphones to old laptops. More efficient data management leads to improved processes and workflows that cross organizational, geographical, and regulatory domains.

Evolving the DX playbook

What allows CIOs to rethink all these areas of transformation are the increasing capabilities enabled by enhanced technologies and coordinated implementation strategies. Rushed implementations can lead to deploying solutions that may not be ready, resulting in a makeshift approach to transformation. This leaves the organization with multiple tools, all geared toward a specific use—with little to no integration or interoperability, plus technical debt from duplicate or overlapping functionality.

This transition from planning to implementation is especially tricky for CIOs and other C-suite stakeholders. IT decision-makers must retain visibility and control of the overall DX effort without being pulled into the countless day-to-day integration tasks and decisions. This can be addressed by developing a DX framework that ensures all new capabilities rolling out are orchestrated and all stakeholders are working together in a seamless fashion. It’s a formalized plan that may include detailed maps and templates of core systems and processes.

The DX framework and the entire modernization effort ideally are supported by a stronger underlying approach to data management—one that breaks down data silos to dramatically improve information access and agility.

The most advanced of these data management environments is known as data fabric. This is when information is no longer locked away in disparate systems and difficult to access in a usable format but rather freely available for collaboration and innovation among any number of stakeholders and development teams in the organization.

Transforming DX's potential

A well-implemented, leading-edge DX initiative dramatically improves the ability of CIOs and their teams to oversee the entire organization with a central process, data, and application hub. This enables the businesses to integrate diverse new and existing solutions, continually iterate both data and architecture upgrades, and support unlimited access and sharing of data.

Taken together, these steps toward more advanced and effective DX will drastically improve operations, security, and value across the enterprise.

[ Learn the non-negotiable skills, technologies, and processes CIOs are leaning on to build resilience and agility in this HBR Analytic Services report: Pillars of resilient digital transformation: How CIOs are driving organizational agility. ]

From automation to DevSecOps, these game-changing technologies are evolving the digital transformation playbook.

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Digital Transformation

RPA

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