Brand consistencyLeave a Comment on Brand guidelines are at the heart of your on-brand culture

Brand guidelines are at the heart of your on-brand culture

These days most people know what a brand is. Or they think they do. People globally recognise the shape of a Coca-Cola bottle, the phrase ‘I’m loving it’, or the Nike Swoosh.

But as all marketers know, brand goes far deeper than a logo or image and in this article we will explore exactly how to create brand consistency, which in turn will help to foster an on-brand culture. We will also look at why this is so important, how you can use brand management software to achieve brand compliance, and the risks if you don’t get your brand culture on point. 

What’s in a brand? 

The logo is just the start – any company needs a clear set of brand guidelines covering everything from use of images to tone of voice and as marketers you will know that there is a lot of detail needed in between — you will need clear direction on how to present dates and numbers, logo placement, use of punctuation, and more.

When you have effective brand guidelines and brand assets — including campaign information and design templates – the marketing team will know exactly how to use words and imagery to communicate your brand consistently and to convey the right look and feel.  

Why is brand consistency important? 

In today’s competitive business landscape, establishing a strong brand identity has become more crucial than ever before. With countless options available to consumers and rapidly evolving market trends, companies need to find ways to stand out from the crowd and make a lasting impression. One key strategy you can’t ignore is by being on-brand – at every touchpoint.

When your brand elements, such as your logo, colour palette, and typography, are consistently applied across all platforms, your audience can quickly identify and distinguish your business from others. This recognition fosters trust and familiarity, making customers more likely to choose your brand over competitors. 

And, when you are maintaining brand consistency across all elements — from visuals to messaging — this can significantly impact your business’ success and help you build a loyal customer base. What’s more, being on-brand helps showcase your unique selling proposition which enables you to differentiate yourself from similar businesses.  

Ultimately, a strong brand identity sets you apart and gives potential customers a reason to choose you over other options. Just make sure you have software that ensures your people actually implement the brand guidelines you worked so hard to establish.

Being on-brand creates customer loyalty 

When customers encounter a brand that delivers a consistent experience, it creates a sense of reliability, dependability and trust. They come to expect a certain level of quality and value, which helps build a strong reputation for your business

Without this, your company will not come across as professional and credible. It’s that familiarity which brings reassurance to the customer that your company will deliver on its promise, regardless of the product or service you offer. You need every image to be precise and the tone accurate, otherwise your customers will find your competitors more attractive.  

The benefits of a deeper connection 

When your brand consistently communicates its values, personality, and purpose, it creates an emotional resonance with your target market. By tapping into their aspirations, desires, or pain points, you can forge a deep connection that goes beyond transactional relationships. 

When customers feel emotionally connected to your brand, they are more likely to become loyal advocates. They become brand ambassadors, sharing their positive experiences with others and fostering word-of-mouth marketing. Consistency in your branding ensures that these advocates have a clear and compelling message to convey, further strengthening brand loyalty — whether they engage with your brand online, visit your physical store, or interact with your social media accounts, they should feel like they are part of a unified brand ecosystem. This consistency not only enhances customer satisfaction but also fosters positive associations with your brand. 

Connecting with staff as part of an on-brand culture 

An on-brand culture goes beyond look and feel and is not just about your customers. It’s about values and this ties into how your employees feel, about what makes your staff, and therefore your company, tick. Think of the brand guidelines – the imagery and tone – as the skin of the company, whilst the culture is the heart. You want everyone to embody the same positive attitude, so ask yourself what it is that has drawn your employees to working for you? What values and beliefs are we tapping into, and what’s your ethos? 

It’s all about employee engagement. Modern working culture frequently sees staff look for a company perspective on diversity (particularly Gen Z) and sustainability, rather than simply the product or service you offer – they want something that chimes with their value system. 

This links to your Employee Value Proposition as employees, and your audience, will be looking at what sets you apart from your competitors, when considering working for, or leaving your company. The danger here is that they may find your competitors more attractive as without a consistent brand and an on-brand culture you will not achieve salience.

Plus, you want them to become brand ambassadors and promote your company favourably and consistently too. All of this is part of a strong employer branding strategy, and a brand management software should support your teams to help you become an employer of choice for the best talent.

Going global while staying local 

Last but by no means least, you need to consider the international nuances for your brand, both in terms of look and feel but also tone and language. This is where you need some expert translation to ensure that your message lands well with your audience, wherever they are internationally, and always remains on-brand.

You will want to ensure that you respect and acknowledge the differences between global and local audiences, whilst still communicating the core brand identity across cultural, regional, and local nuances and languages.

If you want to build an on-brand culture across your enterprise, a brand management platform provides a foundation for your teams worldwide. As part of the Papirfly Platform, you can create this foundation as you educate your people and maintain control. Your brand portal solution is Point, as the starting point of our full suite of products which includes a DAM to manage and access all your brand assets – plus on-brand templating to enable you to achieve brand consistency in all asset creation, salience and in turn, a global on-brand culture.

Product, Thought LeadershipLeave a Comment on Papirfly unveils seamless integration with Ungapped

Papirfly unveils seamless integration with Ungapped

In an exciting development for marketing and brand professionals, Papirfly, the renowned brand management platform, has announced an integration with Ungapped, the user-friendly communication platform equipped with a variety of marketing tools.

 This collaboration promises to streamline brand consistency and enhance user experiences for both Papirfly and Ungapped users.

A hub for marketing excellence

Ungapped is a Swedish digital communication platform that caters to various marketing needs, including email marketing, SMS campaigns, event management, surveys, and marketing automation. The platform is also hosted on GDPR-compliant servers. The new integration allows users to easily pull assets from Papirfly’s Digital Asset Management solution, Place, and integrate them seamlessly into their marketing campaigns in Ungapped.

The integration between Papirfly and Ungapped introduces the ability to find, select, and retrieve assets from Place directly within Ungapped. This integration web plugin bridges the gap between brand management and marketing automation, making it easier than ever to maintain brand consistency throughout marketing materials.

How the integration benefits marketing users

  • Seamless asset retrieval: Users of Ungapped can now seamlessly access assets stored in Place through Papirfly’s integration. This streamlines the workflow, ensuring that marketing materials are consistently on-brand.
  • Time efficiency: With the integration to Papirfly’s Place, marketers can save valuable time by eliminating the need to switch between platforms. This streamlined process allows them to focus on creating engaging on-brand content and campaigns.
  • Brand consistency: Maintaining brand consistency is paramount for businesses. The integration ensures that all assets used within Ungapped adhere to brand guidelines, promoting a cohesive brand identity.
  • Enhanced user experience: Users of both platforms will benefit from the convenience of this integration, resulting in a more user-friendly experience and greater productivity.

In a world where branding and marketing are more critical than ever, the Papirfly-Ungapped integration represents a significant step forward. It empowers businesses to manage their brand with precision while efficiently executing marketing campaigns. With this partnership, users can look forward to a future where brand consistency and marketing automation seamlessly coexist, ultimately driving success and growth for their organisations.

Employer brandLeave a Comment on How to develop and deliver an effective employer brand strategy

How to develop and deliver an effective employer brand strategy

The powerful story you tell about why people should want to work for your brand is like any other captivating narrative – it will be strong in its beginning, middle and end. Hopefully, if you tell it right from the very beginning, the best talent will start to believe your company is the best place for them, want to be right in the middle of your exciting growth plans, and end only after a long and exciting career with you. Making the right choices today could see you soon retelling the story of how you mastered your employer brand strategy – to attract, recruit, and retain top talent.

In this article, we’re going to look at why employer branding is so important, how to achieve success with your strategy, and why not having these elements in place is a mistake. Previously we have explored the 13 steps to developing your employer branding strategy but here we are going to distil them into just three steps – Persona, Positioning, and Proof.

What would happen without an employer branding strategy?

With sites like Glassdoor and Indeed, potential employees now have a range of tools at their disposal to assess companies when job hunting, to see if the business and culture, among other things, are a good fit for them. 84% of jobseekers consider the reputation of a company important and 52% will look at social media channels to get a feel for the company culture.

Consider that without an employer branding strategy you will experience low talent retention and good staff are expensive and timely to replace if the competition looks more attractive to them. And following the pandemic, talent are considering hybrid roles and flexibility far more keenly – so companies who want to tap into this finite resource will need to be transparent, flexible and competitive with their offer. 


First and foremost, you need to audit how your audience perceives your brand. The best way to do this is by assessing social media, company review sites, Google alerts and internal employee feedback. Listening is a vital skill in any communications strategy, and you need to be aware of your reputation if you want to build brand equity.

From here, you want to assess the persona of your target audience and build a profile of your ideal candidate. What sort of personality do they have? What motivates them? Where do they look for their next role and who influences them? These are important considerations if you want to build up that persona to truly get inside the skin of your audience.

What you’re really aiming for is to clearly establish what makes your brand unique. When you truly understand who your audience is, you can then establish what it is about your brand that will tick their job-hunting boxes. It feeds into your employer brand strategy as it tells you why they would choose you above the competition. Is it that your values align with theirs, your company culture, or your social responsibilities? The more your goals resonate with your employees, the more engaged and motivated your workforce will be – which will always have a positive impact on the bottom line.


So, what about positioning? Once you know exactly who you are talking to and what message you need to share, it’s time to consider how you will reach them – what marketing channels will work best for your strategy?You will know the type of social media channels which fit the demographic, which career sites they use and where to advertise. Video is worth considering as it is a powerful medium which can enable you to show familiar faces of the company. You need to post regularly and authentically, considering localised nuances if you are a global company.

Central to your positioning is your Employee Value Proposition or EVP. This tells you exactly how you align your values against those of your employee, with them at the heart. Include here what motivates them. Is it healthcare benefits, flexibility, or bonuses for example? It will be a mixture, and you need to ensure you communicate these messages throughout the recruitment and onboarding processes, and are always available to current staff. Your business will benefit when brand guidelines are all housed within one , – helping you to ensure you’re communicating a strong, consistent brand, which is as much about values as it is about logos.

Recruit retain talent success CTA


What happens if you don’t take these steps? Research shows that staff are 20% more likely to leave a workplace within a year if there is no investment in their future, which is why training and development is absolutely essential, and you have to mean what you say and demonstrate this clearly. It’s one thing to show that your values align, but to truly demonstrate this you need to offer opportunities for growth and in this way you will nurture brand advocates – they will tell their friends and promote your vacancies.

Throughout this process of developing your employer branding strategy, you need to evaluate success. Any successful communications strategy has an internal review at the heart. If you set a benchmark and continue to assess how well your strategy is performing, this can inform your future communications. This includes seeking buy-in across the board. HR professionals, board members, staff, and candidates, all need to be included. Then you can fine-tune against your KPIs and conduct focus groups, so the strategy is continually evolving.

Implementing your employer branding strategy means putting people at the heart of everything you do, as they can be your biggest asset and opportunity for growth, with the right approach. They will become your champions. With Papirfly’s brand management platform, empower your employer branding team to attract, recruit and retain the best people – and celebrate building and being part of a team of champions for your successful global brand. In fact, you can read all about how we helped Unilever deliver employer brand perfection with our platform.

AI, Product, Thought Leadership

AI beyond the hype – Staircases to (AI) Heaven and Hell

We’ve looked at a number of areas where Artificial Intelligence will drive real and meaningful change in this AI-Illuminate series. We’ve looked at how Hollywood has convinced us of eternal doom, we’ve considered how machines will rid us of meaningless tasks, and we’ve discussed ways that Machine Learning might not build Society 2.0 as equitably as we’d like.

But as with all situations, there are two sides to the coin.

The Staircase to (AI) Hell

Let’s start with the depressing take on the journey ahead.  Introducing the Staircase to (AI) Hell.

Beginning with ‘simple automations’ doesn’t feel that scary. Human beings are inherently lazy, we don’t generally like repetitive things, and if there’s a faster way to do something we’ll usually opt for it. Enter the robots! It’s easy to envisage a world where anything even remotely repetitive is simply done by a machine.

Even as we move to the next ‘step’ of the staircase, and we start to see some ‘low priority’ jobs being replaced, most people have little-to-no concern yet. Perhaps because most people discussing the AI debate right now consider their own jobs to be higher priority.

As we approach the step where Deep Learning can do a lot of things better than humans, we end the ‘light blue’ section of this staircase and start entering darker territories.

The first real grey area is the point in time where Deep Learning transfers billions of tasks from humans, replacing hundreds of millions of jobs. We’re no longer ‘just’ talking about the jobs most people think are not theirs – we enter a period of wholesale change with white-collar and blue-collar jobs equally threatened. What do the newly-unemployed do? How do they survive?

As we enter the ‘dark blue’ steps of the staircase we see General Artificial Intelligence (AGI) surpassing most abilities of most humans, which then leads to the point of ‘Singularity’ where machines become too powerful for their human creators to control.

At this point it really is humans vs. robots and, by all accounts, we don’t look set to win.

It is somewhat depressing.

Who can save us?

The Staircase to (AI) Heaven

I believe we can, as is common with many of the debates around AI, look to the past for our saviour. Isaac Newton to be precise. In Newton’s Third Law, he stated that for every action in nature there is an equal and opposite reaction. So perhaps we can turn the Staircase to (AI) Hell into a Staircase of (AI) Heaven? What could that look like?

Well, in Newton-friendly terms, it’s equal and opposite. When we flip the pyramid upside down, we start with the same simple automations that help us humans not have to do the boring things we don’t want to do. This, in itself, can only be a good thing. More efficiency can definitely help us focus on other things. It could likely also be part of the solution to some of our big global problems like waste and the distribution of equitability.

As we progress through the next two steps, there’s a positive to each too.

Complex AI replacing ‘low priority’ jobs is fine if what we mean by ‘low priority’ jobs are jobs humans are not very good at, where it’s dangerous to their health, or where we expend resources doing things unnecessarily. As long as we start to migrate those same displaced people into new, better, roles and / or find ways to replace their income.

Likewise, where AI can do things better than humans, let’s use AI. Of course it makes sense. If a machine is 10x more accurate at doing something, let the machine do it. Where a human+machine combination excels, like in the visual detection of some cancers, then let’s make it happen. Again, we just must not forget to plan for the displaced. Is it time to look at Universal Basic Income (UBI) models again, for example?

Where that displacement of jobs becomes wider and deeper, we do need to be ready. If AI is set to change a billion jobs within the decade, as some academics predict, our policymakers, lawmakers, and politicians need to be working on Plan B now. If we are to leverage the opportunity of the technologies we have created, we need to be ready.

We’ve been here before. The agricultural revolutions of the 19th Century – forever changing what farm labour looked like through the introduction of machinery – are the very reason we’re all able to sit here and read this article when we’d otherwise be out bringing in the harvest so our families could eat. I love the countryside but I’m very grateful for the historic jobs displacement that means I don’t need to grow my own wheat every year.

Daring to dream of AI’s future

The next few steps on the Staircase to AI Heaven are not filled in yet. We don’t know what the future will hold – but we can dare to dream…

Eradicating waste. Making human error a thing of the past, being able to predict things perfectly. Transforming health outcomes. Increasing quality of life for everyone. Curing cancer. Moving beyond fiat money. Driving equitability. Understanding where we come from. Closing the income gap. Working globally as one. People living longer. The end of discrimination. Solving the climate crisis.

It might not all be possible – and certainly not within our lifetimes – but it’s a wonderful AI Heaven to believe in.

Watch our on-demand webinar

AI, Product, Thought Leadership

AI beyond the hype- our Ethical Charter

In part 3 of this series we explored the Three Pitfalls of AI – privacy, replication, and bias. Each pose significant threats to how we live and work today, barriers to mass adoption of machine intelligence, and complex questions about safety and regulation.

That said, the opportunities AI promises are equally significant. We are likely at the start of a fourth industrial revolution and – even if we don’t know exactly how yet – artificial intelligence is going to change a lot (if not everything).

Operating in a new world without new regulation, the onus on companies like Papirfly – building the technology of tomorrow – to self-regulate becomes critical. Good corporate citizenship, acting responsibly, and pursuing opportunities ethically all require guidance and leadership.

To help our people make promises to our customers and our users about how we’ll build our software, we have created our Ethical Charter.

Comprising eight action statements within four ethical themes, it governs how we – as a company – will build technology, and it sets out a pledge for how we will put users at the heart of doing so.

Today we publish it openly.

Papirfly’s Ethical Charter

Be a good corporate citizen when it comes to the rightful privacy of our users

1. We must always obey local, regional (including GDPR), and international privacy laws. Beyond the question of legality, we must always treat users ethically too. This includes creating AI applications that do not invade their privacy, do not seek to exploit their data, do not collect any data without express (and understood) consent, and do not track users outside of our own walled garden. We do not need data from the rest of their activities, so we should not seek to obtain and use it.

2. We do not, as a hard rule, use data to create profiles of our users to facilitate negatively scoring, predicting, or classifying their behaviours. We must never use their personal attributes or sensitive data for any purpose. Neither of these tactics are required for us to make better software for them (which is what we are here to do) and so it is inappropriate. We must always understand where our ethical red line is and ensure everything we do is on the correct side of that.

Ensure we act in an unbiased manner – always – as we’d expect to be treated too

3. We acknowledge that there can be unacceptable bias in all decision making – whether human or machine based. When we create AI applications we must always try to eliminate personal opinion, judgement, or beliefs; whether conscious or otherwise. Algorithmic bias is partially mitigatable by using accurate and recent data so we must always do so. Remember, a biased AI will produce similar quality results as a biased human – “garbage in, garbage out” applies here, always.

4. We must use AI to augment good and proper human decision making. We do not want, or need, to build technology to make automated decisions. As in other areas of our business, like recruitment, we have not yet proven the strength of affirmative action (sometimes called positive discrimination) and, so, mathematical de-biasing is not considered an option for us. As such, all decision-making inside any application must include humans. Their skillsets, experience, and emotional intelligence can – and should – then be added to by AI.

5. We work to the principle of “you get out what you put in” and understand that in order to build technology for the future we can neither only look to the past (using out of date data, for example) nor build AI on top of existing human biases. Gender, ethnicity, age, political and sexual orientation bias (this list is not exhaustive) are all discriminatory and we must proactively exclude this human trait of today and yesterday in our search for technology solutions of tomorrow.

Build in the highest level of explainability possible, because output is important

6. We are not interested in only building black box solutions. If we can’t create defendable IP without doing so then we’re not doing our jobs properly. We want to, wherever possible – and always when possible – be able to explain, replicate, and reproduce the output of a machine we have built. We owe this to our users and it’s also how we’ll get better at what we do. The better we understand what we are building the quicker we can evolve it.

7. We actively subscribe to the “right to explanation” principle championed by Apple, Microsoft, and others. We must build applications that give users control over their personal data, determine how decisions have been made, and be able to easily understand the role their data has in our product development. We can do this without affecting our ability to defend our IP and, therefore, should do so as a default. Whilst full replication is not always possible (within deep neural networks, for example) our mission – and policy – is to do as much as we feasibly can.

Overall, our task is simple – we must build technology that is designed to do good

8. Technology is a wonderful and powerful thing. As a software company, we must believe that. But behind any, and every, application for good there are usually opportunities for evil too. As we depend more and more on AI it will take on a bigger role inside our organisation. As we craft and hone it, it is our responsibility to put ethics at the forefront and build responsibly. For now, we are our own regulators. Let’s be the best regulators we can be.

Moving forward with ethics at the heart of AI innovation

At Papirfly we have defined an Ethical Charter that governs what technology we build, how we build it, and the ethical parameters within which we build it. In Part 5 of this series we’ll provide a comprehensive analysis of various scenarios related to AI, highlighting both the benefits (“heavens”) and potential drawbacks (“hells”). This balanced perspective will present a clear view of AI’s capabilities and limitations.

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AI, Product, Thought LeadershipLeave a Comment on AI beyond the hype – The 3 pitfalls of AI

AI beyond the hype – The 3 pitfalls of AI

You don’t have to look far to feel the air of AI-scaremongering. Robots coming for our jobs, AGI (General Artificial Intelligence) surpassing human ability, reaching the point of ‘Singularity’ – the hypothesis that AI will become smarter than people and then be uncontrollable, and the end of humankind as we know it. Movies like The Terminator, Minority Report, and Ex Machina have Hollywoodified Earth’s surrender to technology for years now.

When you ask corporate leaders about the risks AI present to their organisations, you tend to get similar answers based on similar themes:

  • What about copyright and intellectual property?
  • What about job displacement and human capital?
  • Are we at the start of a machine-led world?
  • Are we at risk of machine intelligence replacing human intelligence?
  • How do we compete against infallible machine intelligence?
  • How do we move fast enough to mitigate the risk of being out-run?
  • Who wins in the end – us, our competitors, new entrants, or AI generally?
  • Who can be trusted to regulate this new world?

Each of these questions can be unravelled to create opportunity alongside risk, but many leaders currently find it hard to differentiate. There is so much noise. There is still a talent gap – it’s estimated we need 10x the computer science graduates we have today in order to meet the hiring plans already announced by major software companies. The rapidity of change is increasing faster than existing operational models, such as fiscal years or quarterly reporting, were designed for.

This means, in all likelihood, that we must look elsewhere for a rational and unencumbered view. Let’s look at what academics have reached agreement on.

Academics don’t routinely agree with each other but for the past decade thought leaders from the biggest and best technology education institutions (including Massachusetts Institute of Technology [MIT], University of Oxford, Stanford University, Indian Institute of Technology, National University of Singapore, etc) have settled on the Three Pitfalls of AI as being Privacy, Replication, and Bias.


Defined as the ability of an individual or group to seclude either themselves (or information about themselves), and thereby be selective in what they express, privacy is a phrase we’re all familiar with. The domain of privacy partially overlaps with security, which can include the concepts of appropriate use and protection of information.

But the abuse of privacy can be more abstract. Consider the (existing) patents that connect social media profiles with dynamic pricing in retail stores. The positioned use case is usually a discount presented to a shopper because the retailer’s technology knows – from learned social media data – that they are likely to buy if presented with a coupon or offer. This feels win-win for both parties and therefore the data shared feels like a transactional exchange rather than a privacy intrusion.

However, where that same technology can be used to inflate the price of a prescription for antidepressants – because the data tells the retailer’s system that the shopper is likely struggling with their mental health – it quickly becomes apparent that the human cost of privacy abuse could be very high indeed.

Privacy is considered one of the three pitfalls of AI because data (and so often personal data) is so intrinsically linked to machine intelligence’s success. The conversation around who owns that data, how that data should / should not be used, how to educate people about the importance of data, and how to give users more control over the data has been happening in pockets (but far from all) of society for a long time. As AI advances, it’s widely acknowledged that this area has to evolve in tandem.


The inability to replicate a decision made by Al – often referred to as a ‘black box’ – occurs when programmers and creators or owners of technologies do not understand why their machine makes one decision and not another.

Replication is essential to proving the efficacy of an experiment. We must know that the results a machine produces can be used consistently in the real world, and that they didn’t happen randomly. Using the same data, the same logic, and the same structure, machine learning can produce varying results and / or struggle to repeat a previous result. Both of these are problematic – and can be particularly troublesome when it comes to algorithms trained to learn from experience (reinforcement learning) where errors become multiplied.

The ‘black box’ approach is often excused by claiming IP protection or ‘beta’ status of products. But the prolonged inability to interrogate, inspect, understand, and challenge results from machines leads to an inability for humans to trust machines. Whether that’s confusion about how a lender has credit-scored your mortgage application, or something even more serious like not being able to prove that a prospective employer has used machine learning to discriminate against a candidate.

Replication is considered one of the three pitfalls of AI because we need to know we can trust AI. For us to trust it we need to be able to understand it. To be able to understand it we need to be able to replicate it.


“A tendency, inclination, or prejudice toward – or against – something or someone” is how bias is usually defined. Today, Google has more than 328m results when you search for “AI bias”. Unfortunately AI and bias seem to go hand-in-hand with a new story about machine intelligence getting it (very) wrong appearing daily.

As the use of artificial intelligence becomes more prevalent, its impact on personal data sensitive areas – including recruitment, the justice system, healthcare settings, and financial services inclusion – the focus on fairness, equality, and discrimination has rightly become more pronounced.

The challenge at the heart of machine bias is, unsurprisingly, human bias. As humans build the algorithms, define training data, and teach machines what good looks like, the inherent biases (conscious or otherwise) of the machines’ creators become baked-in.

Investigative news outlet ProPublica has shown how a system used to predict reoffending rates in Florida incorrectly labelled African American defendants as ‘high-risk’ at nearly twice the rate it mislabeled white defendants. The system didn’t invent this bias – it extrapolated and built upon assumptions programmed by its creators.

Technologists and product leaders like to use the acronym GIGO – ‘Garbage In, Garbage Out’ – and it absolutely applies here. When we train machines to think, all of the assumptions we include at the beginning become exponentially problematic as that technology scales.

Replication is considered one of the three pitfalls of AI because technology is often spoken of as being a great ‘leveller’, creating opportunities, and democratising access. But so long as AI bias is as bad as, or worse than, human bias, we will in fact be going backwards – with large sections of society disadvantaged.

Responding to AI’s challenges

Each of these Three Pitfalls of AI are serious and they have attracted a lot of attention – including from the leaders of the very companies at the forefront of AI’s development and evolution. When more than 1,100 CEOs wrote the now-infamous open letter calling for a halt to AI development they were essentially asking for time for humans to catch up and think about the possible consequences of our actions.

There are further questions about regulation – with lawmakers struggling to keep up with the rate of change. Trust of politicians remains stubbornly low globally and the public is also hesitant to trust a small group of technology company billionaires with what realistically could be existential threats to parts of how we live today. But self-regulation is where we are at currently and that means it comes down to individual technology creators to build responsibly and ethically.

At Papirfly we have defined an Ethical Charter that governs what technology we build, how we build it, and the ethical parameters within which we build it. In Part 4 of this series we’ll share our Ethical Charter and demonstrate how it works in our company.

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AI, Product, Thought LeadershipLeave a Comment on AI beyond the hype – “AI was invented in December 2022…right?”

AI beyond the hype – “AI was invented in December 2022…right?”

Cast your mind back to the end of last year and think about your Instagram, Facebook, and Twitter (as it still was) feeds. If they were anything like mine they were likely full of friends’ AI-generated photos. Or, at least, the ones that made them look smarter, prettier, taller, thinner, etc. Generative AI had exploded into the mainstream.

You could be forgiven for thinking it was invented around then too – and are possibly surprised to know that Artificial Intelligence is as old as the aunties and grandmothers who asked you about it around the dining table at Christmas 2022.

Putting AI to the test

AI is around 70 years old. Its roots can be traced back to Alan Turing (of ‘The Imitation Game’ fame), the British WWII codebreaker. Turing was a leading mathematician, developmental biologist, and a pioneer in the field of computer science. His earliest work created the foundations for AI as we know it. His eponymous test, The Turing Test (created in 1950), tests a machine’s ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human.

Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another.

The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine’s ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine’s ability to give correct answers to questions, only on how closely its answers resembled those a human would give.

A thought experiment

The Golden Age of AI followed, spanning roughly 1956-1976. During this period, scientists and researchers were optimistic about the potential of AI to create intelligent machines that could solve complex problems by matching human intelligence – or even surpassing it.

Whilst the era fizzled out it delivered many a ‘first’ that still holds value today. ChatGPT’s ‘great-great-grandmother’ could be considered to be ELIZA – one of the first chatbots (then called ‘chatter bots’) and an early passer of The Turing Test, which was created from 1964 to 1966 at MIT by Joseph Weizenbaum.

Moving into the next decade, John Searle (a prominent American philosopher) set the tone with his Chinese Room Experiment theory. Searle proposed the Chinese Room Experiment as an argument against the possibility of Al, aiming to illustrate that machines cannot have understanding. 

Searle uses the following scenario to demonstrate his argument:

“Imagine a room in which a man, who understands no Chinese, receives, through a slot in the door, questions written in Chinese. When he receives a question, the man carefully follows detailed instructions written in English to generate a response to the question, which he passes back out through the slot. Now suppose the questions and responses are part of a Chinese Turing Test, and the test is passed”.

Chess and penguins

The years that followed this ’downer’ of a start to the 1980s were low in ambition and confined to what we now look back as ‘Behavioural AI’. Knowledge based systems, sometimes called ‘expert systems’, were trained to reproduce the knowledge and / or performance of an expert in a specific field. They mostly used the “if this then that” logic flow and they didn’t always get it right – with the identification of penguins (birds but flightless birds) being an oft-cited example of basic errors of the time.

This era produced a few big wins – especially in the efficiency space, like Digital Equipment Corporation’s ‘RI’ application which saved it $40m per year by optimising the efficiency of computer system configurations. But it was prior to the advances of computerised automation which really made corporate adoption commonplace. It’s also acknowledged to be the period of time that birthed the first bias in AI.

A lot happened in the world of AI in the 1990s – seeing major advances in defence, space, financial services, and robotics. So it’s perhaps surprising that most AI historians and computer scientists point to the same turning point for machine intelligence. In 1996 ‘Deep Blue’, a chess-playing computer from IBM, beat then-champion Garry Kasparov. Prior to this, chess had been singled out as a ‘frontier’ for machine vs. human intelligence, with many people believing the human brain to be the only one capable of mastering a game with between 10¹¹¹ and 10¹²³ moves. (A ‘googol’, being the inspiration behind Google’s name, is 10 to the 100th power, which is 1 followed by 100 zeros). Machine intelligence had arrived.

A new era emerges

As the use of computers in domestic settings proliferated, there was an exponential surge in Internet usage in the mid-1990s, with the last few years of the decade renowned today for the dotcom bubble (1995–2000) and its ultimate implosion. Throughout this time AI took a backseat in social contexts, despite already starting to power many consumer applications and early-version software, websites, and applications. Commercially the focus was on automation and efficiency. Neither of which were particularly “sexy” or fun.

Enter…the self-driving car. A longheld obsession and science fiction staple, the period between March 2004 and October 2005 was to become the start of a whole new age. The DARPA Grand Challenge was a competition for autonomous vehicles funded by the Defense Advanced Research Projects Agency, the research lead within the United States Department of Defense. The race saw 21 teams, each with their own self-driven vehicle, prepare to compete in a race spread out over 150 miles / 240km.

A grand total of zero entrants finished the race in 2004. But in the 2005 race, five vehicles successfully completed the course. Of the 23 entrants, all but one surpassed the 7.32 miles / 11.78 km distance completed by the best vehicle in the 2004 race. The winner on the day was Stanley (named by its entrants, the Stanford Racing Team) but the overall winner was AI itself, with optimism levels rallying and the machine intelligence conversation building in reach and volume.

Humanoid robots and sci-fi dreams

In the late 2000s, AI entered its ‘modern era’. A number of humanoid robots brought AI closer to science fiction, driverless car projects became abundant, AI was being built into consumer and commercial applications, and the Internet of Things (IoT) emerged – with the ratio of things-to-people growing from 0.08 in 2003 to 1.84 in 2010 alone.

The 2010s were really where we saw mass proliferation of AI in society. When we think about the mainstream tech we take for granted today much of it was born (or matured) in this decade. Virtual assistants like Siri. Machine learning tools. Chatbots capable of human-quality conversation. Mobile phone use cases. Photography aids. In-car innovations like satnav and cruise control. Smart watches. Smart appliances. Real-time share trading platforms that everyone can use, not just financial giants. Even the humble product recommendation engine. They all use AI.

We arrived in to the 2020s with 70 years’ build-up in artificial intelligence, machine learning, and deep learning. The past few years have seen significant advances and the next few will undoubtedly too.

Embracing AI’s evolution

When you next ask ChatGPT to write that report for you, when you use Papirfly’s Generative AI to create hundreds of illustrations in an instant, or you think about the potential pitfalls of AI (we’ll address these in an upcoming article) do remember that we’re not dealing with a brand new toy here.

Instead, we are working with technology that started its journey in the 1950s. A journey that has seen an amount of change its early creators could never have predicted in their wildest dreams, and one that is likely to transform almost every aspect of human life in the next decade.

Watch our on-demand webinar

Brand management, BrandsLeave a Comment on How to unleash brand management excellence from one platform

How to unleash brand management excellence from one platform

In a dynamic global marketplace, maintaining a consistent and captivating brand image across diverse regions and channels is no easy feat. For countless global enterprises, brand management poses different challenges depending on size, industry, and the complexity of the organisation – which only increases as a brand grows.

Navigating the specific challenges each brand faces is significantly reduced when teams that need to govern and drive the brand  – whether in a corporate, employer branding, or marketing operations capacity – know that the strategy they put in place is supported by the tools their enterprise chooses to invest in as part of their techstack ecosystem.

In this article, we’ll see how some of the world’s most recognisable brands have done that with an all-in-one brand management platform.

Understanding brand management challenges

For a brand and its people to engage and grow a loyal customer base, there are several things to consider. These include having an identity that is clear and consistent, a business that is seen as responsive to trends and events, and communications that resonate with customer expectations – exceeding them whenever possible. Not considering these elements, and the technology that will help you achieve this, will make it less likely customers see you as a standout choice in a sea of competitors.

Business challenges will not go away – it’s what makes work life exciting. Yet when fragmented branding strategies, ineffective approval processes, and difficulties in upholding brand compliance become the norm for so long, hitting growth goals becomes unlikely. 

Building an on-brand culture through an all-in-one centralised brand management platform turns what were once formidable barriers into problems of the past, and offers solutions for key areas for global enterprises to unleash the brilliance of their brand and their people into the world. It can do this in several ways, depending on the most pressing business priority.

Global brand consistency delivered by all teams


With no central system in place for coordinating brand assets, staff at Unilever were spending significant amounts of time reviewing designs by local teams. At the same time, these local teams were spending valuable time and resources creating their assets from scratch, then waiting for them to be signed off. Many were also often relying on external agencies for their assets, eating into budgets and further slowing them down.

Unilever’s leadership gained a birds-eye view of how assets were being used globally, ensuring brand consistency and message alignment. Custom workflows and approval processes were easily established for edge-cases, improving communication and collaboration between central and local teams. This streamlined approach empowered local markets to deliver Unilever’s purpose-driven brand message effectively and efficiently – eliminated the need for external creative agencies, reducing costs further.

Helly Hansen

Brand management for Helly Hansen was significantly improved in several ways. By offering a seamless global brand management solution that combined online brand guidelines, Digital Asset Management (DAM), and online templates, Papirfly ensured that Helly Hansen could maintain a consistent brand voice and image across all markets and stakeholders. This allowed them to secure one brand identity, essential for a consumer brand with a massive distribution and sales network like Helly Hansen.

Serving as a one-stop-shop for all marketing needs, Papirfly’s platform ensured the brand could be served as intended, catering to marketing teams, employees, branded stores, resellers, and local offices to activate it across every channel. This centralised approach increased efficiency and reduced the time wasted on manual processes, ensuring that tight deadlines for seasonal campaigns were met effortlessly.

Consistent employer branding on a global scale


Before implementing Papirfly, IBM faced the challenge of ensuring its brand identity was communicated consistently across its 65 regions. Each region had its own marketing and recruitment teams, leading to variations in branding and marketing efforts. With Papirfly’s centralised hub for asset standards, guidelines, and design templates, IBM was able to enforce unbreakable brand guidelines and ensure that all marketing and recruitment materials were on-brand. This allowed IBM to present a unified and modern employer brand, appealing to younger generations of potential employees worldwide.


It was a similar story with another huge brand – Vodafone – achieving total brand clarity, improving consistency in employer brand communications, and reducing the need for central approvals. Our platform enabled the company to digitise its branding efforts, appeal to tech-savvy young employees, and focus on delivering an authentic and engaging message about working at Vodafone. By transforming from a “telco to techno” brand, Vodafone aligned its historic telecoms business with modern technological capabilities, improving its ability to attract quality hires and support its evolving digital business. The partnership with Papirfly allowed Vodafone to continue exploring further digital transformation opportunities to enhance talent attraction and skills development in the future – which we’re excited to continue doing to this day.

Combining central marketing and local execution


Utilising seamless automation and centralisation of responsibilities, BMW Northern Europe empowered a more efficient and powerful execution of the brand for local dealers. This streamlined communication and enabled better coordination between the regional office and the local dealers, decreasing time to market and avoiding bottlenecks.

With our all-in-one brand management platform providing a digital foundation to access and adapt marketing collateral from – used by all stakeholders including creative agencies, dealers, and employees – complete accessibility and 100% consistency in all marketing efforts was possible. It was felt that local tailoring while maintaining connection with the core brand and corporate strategies was an essential for a brand of BMW’s profile.

Thon Hotels

Thon Hotels streamlined and structured its marketing operations in a more efficient way with Papirfly’s platform, achieving brand consistency, and improving internal communications. The platform’s ease of use and capabilities impressed both leaders and hotel staff, resulting in a more professional and effective brand presence across all hotels.

Before implementing Papirfly, Thon Hotels faced challenges in coordinating its brand identity across 70 sites and dealing with inefficient inter-departmental communication. The core marketing team struggled to implement new brand guidelines, and hotels often created ad-hoc assets with inconsistent results. Empowering hotel staff to create on-brand materials quickly while centralising all activities and automatically implementing the new brand guidelines across all sites, inconsistencies and errors were eliminated.

Stay ahead with game-changing brand management

Papirfly’s comprehensive platform offers a suite of essential products that work seamlessly together, and can integrate with the wider ecosystem of your enterprise. Our product suits allows you to:

  • One home for your brand
    Educate your people on brand guidelines. Control how your brand is used. Build an on-brand culture for your teams from one online portal.
  • Digital Asset Management
    Manage all files in a powerful DAM. Share assets with ease across your business. Provide one single source of truth to your entire enterprise.
  • On-brand design templates
    Create unlimited enterprise assets. Activate your brand using on-brand design templates. Unleash your brand across all channels, in any language.
  • Campaign execution tools
    Plan and execute campaigns with complete control. Collaborate with efficient workflows, built for your needs. Increase agility for teams everywhere.
  • Enterprise-grade analytics
    Measure campaign success and brand adoption. Optimise brand strategy for better results. Gain insights from a user, team, region and global level.
  • Seamless integrations
    Integrate Papirfly with your tech stack. Give every team a seamless user experience when using our platform as part of your ecosystem.

Empower your people to unleash your brand

In a fast-paced, interconnected world, global brands cannot afford to compromise on brand management. Papirfly has proven to be the beacon of hope, guiding leading brands towards brilliance. Join the ranks of Unilever, Helly Hansen, Vodafone, IBM, BMW, Thon Hotels, and over 600 more global brands, and work with Papirfly to transform your brand management abilities – as we innovate the future of brand management excellence together.

Brand managementLeave a Comment on Changing the game of brand management at Papirfly

Changing the game of brand management at Papirfly

Today marks a significant shift in Papirfly’s vision for empowering enterprises to give their people the tools to activate their brands – everywhere.

Having delivered innovative brand management solutions for over 20 years, we’ve consolidated the 32 products we have built over this time to create a single user interface, giving our customers access to the full range of product functionalities, simplifying their operations and empowering them with an all-in-one platform – offering the ultimate brand management experience.

What does this mean for you?

Watch our launch video to hear from our Product team on what you can expect from Papirfly as we continue to support brands in the increasingly challenging landscape of brand management – as we endeavour to make things as simple as possible.

A customer-centric approach for unparalleled possibilities

At Papirfly, our customers are at the heart of everything we do. Whilst we may refer to this moment as Unification, this is our new normal – improving brand management software to the point that our customers can access an array of possibilities that were previously unattainable. We understand the challenges brands and teams face, and we meet those challenges head on with a mindset of constant innovation for our customers.

Our suite of enterprise-grade products

Gone are the days of navigating through multiple disparate MarTech solutions. Instead, Papirfly offers a unified platform that allows our customers to centralise their brand management efforts, reducing complexity and enhancing efficiency. By relying solely on Papirfly, they can unlock new levels of productivity and creativity with our comprehensive suite of products:


Support global teams to understand your brand, through clear guidelines, official assets, core values, and more from one online access point. Go local with unique hubs with local languages and nuances.


Centralise all assets with a dedicated DAM solution, categorising content for global and local usage in one secure place for all approved material. Ensure every location has assets that serve their unique audience nuances.


Guarantee 100% brand consistency with design templates aligned to brand guidelines and produce infinite studio-quality digital, print and video assets. Empower everyone to personalise to their audience using localised images, video and text options.


Achieve your bird’s-eye view of all campaigns and activities, displaying status, budgets, contacts, and official design templates for use. Ensure every location utilises workflows that drive campaign responsivity.


Analyse marketing activity via your dashboard, delivering reports and data across your business. Ensure local sites get feedback on best-performing content across the business, and give them data to let them know when their efforts are driving brand strategy success.


Papirfly’s integrations mean our platform works seamlessly with your agency tech stack removing hacks and workarounds, improving productivity and organisational efficiency across the business.

Collaborating for the Future

The future of Papirfly is a collaborative endeavour. We actively engage with our customers to shape the direction of our platform. Through direct user feedback and the establishment of a customer council, we have gathered, and will continue to collate valuable insights and that guide our development efforts. By involving our customers in the innovation process, we ensure that our platform remains future-proof and adaptive to the evolving brand management landscape. Together, we co-create a platform that empowers our customers to thrive in an ever-changing business environment, even as their own enterprise grows in complexity.

Empowering people to unleash their brands

While we are excited about this launch moment, this really is just the start of a new era at Papirfly – and we can’t wait to continue the journey with our existing customers, as we continue to welcome new brands to reach new heights of success.

Our commitment to revolutionising brand management drives our pursuit of a unified platform. You’ll be hearing much more about the individual Products of With Papirfly’s unified platform, we embark on a transformative journey, unlocking the power of brands and revolutionising the way they are managed.

Product, Thought LeadershipLeave a Comment on Managing GDPR compliance in Digital Asset Management – the role of a GDPR manager tool for handling consent

Managing GDPR compliance in Digital Asset Management – the role of a GDPR manager tool for handling consent

DAM products and their relation to data management and GDPR

As businesses become increasingly reliant on digital assets, managing data and ensuring its privacy has become more important than ever. One of the ways companies are doing this is through digital asset management (DAM) systems, which can store and organise vast amounts of digital files. However, as these systems become more sophisticated, they can also become more complex, and managing the privacy of the data stored within them can be a significant challenge. This is where a GDPR manager comes in.

  • The GDPR, or General Data Protection Regulation, is a European Union law that sets out guidelines for the handling of personal data.
  • This law applies to any company that processes personal data, regardless of whether it is located within the EU or not.
  • The GDPR manager is responsible for ensuring that a company’s DAM system is in compliance with this law.

Digital asset management (DAM) systems are becoming increasingly important for businesses that deal with large amounts of digital files. However, with this increased use comes a greater need for data privacy and compliance with regulations such as the General Data Protection Regulation (GDPR). To address this need, some DAM systems include a GDPR manager tool that allows companies to manage consent for individuals who appear in photos uploaded to the DAM.

How Papirfly’s DAM can ensure company compliance to GDPR

The GDPR manager in our DAM enables users to create “photo sessions” and handle consents from the individuals depicted in the photos. These individuals are referred to as “data subjects” under the GDPR. The GDPR manager tool allows users to store information about data subjects and their consent status, providing a consent overview that displays a list of all persons who have confirmed consent or are pending.

The GDPR manager’s primary responsibility is to ensure that the company is collecting and storing personal data in compliance with the GDPR. This means that data must be collected for a specific purpose and individuals must be informed about the collection and use of their data. The GDPR manager tool allows users to easily manage consent and ensure that data subjects are aware of how their personal data will be used.

The GDPR manager tool also allows users to monitor the consent status of data subjects and track any changes in consent over time. This is particularly important in cases where individuals withdraw their consent, as companies must ensure that the data subject’s personal data is removed from the DAM system in a timely manner.

Finally, the GDPR manager tool can be used to provide training to employees on GDPR compliance as it relates to the handling of personal data in the DAM system. This may involve providing guidance on how to manage consent and how to respond to requests from data subjects regarding their personal data.

GDPR compliance is key in digital asset management and consent management

The GDPR manager tool in our DAM plays a crucial role in ensuring that companies comply with the GDPR when handling personal data. By providing an easy-to-use tool for managing consent, tracking changes in consent status, and providing training to employees, companies can ensure that they are protecting the privacy of data subjects and avoiding any potential breaches of the GDPR.